diff --git a/.github/workflows/ci-build-manual-onnx.yml b/.github/workflows/ci-build-manual-onnx.yml new file mode 100644 index 0000000000..dd03ee2903 --- /dev/null +++ b/.github/workflows/ci-build-manual-onnx.yml @@ -0,0 +1,79 @@ +name: Build and push an ONNX docker image + +# This workflow builds the lightweight ONNX/Wapiti-only Docker image +# (no Python/DeLFT/TensorFlow dependencies) + +on: + push: + branches: + - feature/onnx-models + workflow_dispatch: + inputs: + custom_tag: + type: string + description: Docker image tag + required: true + default: "latest-onnx" + +jobs: + build: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v5 + with: + fetch-tags: true + fetch-depth: 0 + - name: Set up JDK 21 + uses: actions/setup-java@v5 + with: + java-version: '21' + distribution: 'temurin' + cache: 'gradle' + - name: Build with Gradle + run: ./gradlew build -x test + + docker-build-onnx: + needs: [ build ] + runs-on: ubuntu-latest + + steps: + - name: Create more disk space + run: sudo rm -rf /usr/share/dotnet && sudo rm -rf /opt/ghc && sudo rm -rf "/usr/local/share/boost" && sudo rm -rf "$AGENT_TOOLSDIRECTORY" + - uses: actions/checkout@v5 + - name: Build and push + id: docker_build + uses: mr-smithers-excellent/docker-build-push@v5 + with: + username: ${{ secrets.DOCKERHUB_USERNAME_LFOPPIANO }} + password: ${{ secrets.DOCKERHUB_TOKEN_LFOPPIANO }} + image: lfoppiano/grobid + registry: docker.io + pushImage: true + tags: latest-onnx, ${{ github.event.inputs.custom_tag || github.sha }} + dockerfile: Dockerfile.onnx + - name: Image digest + run: echo ${{ steps.docker_build.outputs.digest }} + - name: Docker Image Summary + run: | + echo "## 🐳 Docker Image Uploaded Successfully" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "**Image Details:**" >> $GITHUB_STEP_SUMMARY + echo "- **Registry:** docker.io" >> $GITHUB_STEP_SUMMARY + echo "- **Image:** lfoppiano/grobid" >> $GITHUB_STEP_SUMMARY + echo "- **Type:** ONNX/Wapiti only (lightweight, no Python/DeLFT)" >> $GITHUB_STEP_SUMMARY + echo "- **Tags:**" >> $GITHUB_STEP_SUMMARY + echo " - \`latest-onnx\`" >> $GITHUB_STEP_SUMMARY + echo " - \`${{ github.event.inputs.custom_tag || github.sha }}\`" >> $GITHUB_STEP_SUMMARY + echo "- **Digest:** \`${{ steps.docker_build.outputs.digest }}\`" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "**Features:**" >> $GITHUB_STEP_SUMMARY + echo "- ONNX Runtime for deep learning models (CPU only)" >> $GITHUB_STEP_SUMMARY + echo "- Wapiti CRF for traditional models" >> $GITHUB_STEP_SUMMARY + echo "- No Python, TensorFlow, or DeLFT dependencies" >> $GITHUB_STEP_SUMMARY + echo "" >> $GITHUB_STEP_SUMMARY + echo "**Usage:**" >> $GITHUB_STEP_SUMMARY + echo "\`\`\`bash" >> $GITHUB_STEP_SUMMARY + echo "docker pull lfoppiano/grobid:latest-onnx" >> $GITHUB_STEP_SUMMARY + echo "docker run -t --rm --init -p 8070:8070 -p 8071:8071 lfoppiano/grobid:latest-onnx" >> $GITHUB_STEP_SUMMARY + echo "\`\`\`" >> $GITHUB_STEP_SUMMARY diff --git a/.gitignore b/.gitignore index 35526b5247..498d6a05cd 100644 --- a/.gitignore +++ b/.gitignore @@ -89,3 +89,5 @@ Dockerfile.dataseer Dockerfile.software Dockerfile.datastet .run + +.kotlin \ No newline at end of file diff --git a/Dockerfile.crf b/Dockerfile.crf index 2199240af8..5982cc37d1 100644 --- a/Dockerfile.crf +++ b/Dockerfile.crf @@ -49,8 +49,9 @@ RUN rm -rf grobid-home/lib/lin-32 RUN rm -rf grobid-home/lib/win-* RUN rm -rf grobid-home/lib/mac-64 -# cleaning Delft models -RUN rm -rf grobid-home/models/*-BidLSTM_CRF* +# cleaning Delft and ONNX models +RUN rm -rf grobid-home/models/*-BidLSTM* +RUN rm -rf grobid-home/models/*.onnx ENV GROBID_SERVICE_OPTS="-Djava.library.path=grobid-home/lib/lin-64:grobid-home/lib/lin-64/jep" diff --git a/Dockerfile.onnx b/Dockerfile.onnx new file mode 100644 index 0000000000..764ebf9d1e --- /dev/null +++ b/Dockerfile.onnx @@ -0,0 +1,117 @@ +## Docker GROBID image using ONNX models and/or Wapiti CRF models +## This is a lightweight image without Python/TensorFlow/DeLFT/JEP dependencies +## Uses ONNX Runtime (CPU only) + +## See https://grobid.readthedocs.io/en/latest/Grobid-docker/ + +## usage example with version 0.8.0: +## docker build -t grobid/grobid:0.8.0-onnx --build-arg GROBID_VERSION=0.8.0 --file Dockerfile.onnx . + +## run: +## docker run -t --rm --init -p 8070:8070 -p 8071:8071 grobid/grobid:0.8.0-onnx + +# ------------------- +# build builder image +# ------------------- + +FROM eclipse-temurin:21-jdk AS builder + +USER root + +RUN apt-get update && \ + apt-get -y upgrade && \ + apt-get -y --no-install-recommends install unzip git python3 python3-pip + +WORKDIR /opt/grobid-source + +# gradle +COPY gradle/ ./gradle/ +COPY gradlew ./ +COPY gradle.properties ./ +COPY build.gradle ./ +COPY settings.gradle ./ + +# git +COPY .git/ ./.git + +# source +COPY grobid-home/ ./grobid-home/ +COPY grobid-core/ ./grobid-core/ +COPY grobid-service/ ./grobid-service/ +COPY grobid-trainer/ ./grobid-trainer/ + +# cleaning unused native libraries before packaging +RUN rm -rf grobid-home/pdf2xml +RUN rm -rf grobid-home/pdfalto/lin-32 +RUN rm -rf grobid-home/pdfalto/mac-64 +RUN rm -rf grobid-home/pdfalto/mac_arm-64 +RUN rm -rf grobid-home/pdfalto/win-* +RUN rm -rf grobid-home/lib/lin-32 +RUN rm -rf grobid-home/lib/win-* +RUN rm -rf grobid-home/lib/mac-64 +RUN rm -rf grobid-home/lib/lin-64/jep + +# Use ONNX configuration (no DeLFT models) +RUN rm grobid-home/config/grobid.yaml && \ + mv grobid-home/config/grobid-onnx.yaml grobid-home/config/grobid.yaml + +RUN ./gradlew clean assemble --no-daemon --info --stacktrace + +# Preload embeddings in raw float32 format for ONNX inference +# Using standalone script that doesn't require DeLFT +RUN pip3 install --no-cache-dir --break-system-packages lmdb requests +COPY grobid-home/scripts/preload_embeddings_standalone.py . +COPY grobid-home/config/resources-registry.json . +RUN python3 preload_embeddings_standalone.py --registry ./resources-registry.json + +WORKDIR /opt/grobid +RUN unzip -o /opt/grobid-source/grobid-service/build/distributions/grobid-service-*.zip && \ + mv grobid-service* grobid-service +RUN unzip -o /opt/grobid-source/grobid-home/build/distributions/grobid-home-*.zip && \ + chmod -R 755 /opt/grobid/grobid-home/pdfalto + +# Move preloaded embeddings to final location +RUN mkdir -p /opt/grobid/data/db && \ + mv /opt/grobid-source/data/db/* /opt/grobid/data/db/ + +# ------------------- +# build runtime image +# ------------------- + +FROM eclipse-temurin:21-jre + +# setting locale +ENV LANG=C.UTF-8 + +# Install minimal runtime dependencies +RUN apt-get update && \ + apt-get -y --no-install-recommends install \ + libxml2 libfontconfig \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* + +WORKDIR /opt/grobid + +COPY --from=builder /opt/grobid . + +# Add Tini +ENV TINI_VERSION=v0.19.0 +ADD https://github.com/krallin/tini/releases/download/${TINI_VERSION}/tini /tini +RUN chmod +x /tini +ENTRYPOINT ["/tini", "-s", "--"] + +WORKDIR /opt/grobid + +ENV JAVA_OPTS="-Xmx4g --add-opens=java.base/java.lang=ALL-UNNAMED --add-opens=java.base/java.nio=ALL-UNNAMED --add-opens=java.base/sun.nio.ch=ALL-UNNAMED --add-opens=java.base/java.io=ALL-UNNAMED" + + +CMD ["./grobid-service/bin/grobid-service"] + +ARG GROBID_VERSION + +LABEL \ + authors="The contributors" \ + org.label-schema.name="GROBID" \ + org.label-schema.description="Image with GROBID service (ONNX/Wapiti only, no DeLFT)" \ + org.label-schema.url="https://github.com/kermitt2/grobid" \ + org.label-schema.version=${GROBID_VERSION} diff --git a/build.gradle b/build.gradle index 7311b05eb9..bb778ba54a 100644 --- a/build.gradle +++ b/build.gradle @@ -24,7 +24,7 @@ def getJavaLibraryPath = { } } else if (Os.isFamily(Os.FAMILY_UNIX)) { jepLocalLibraries = "${rootProject.rootDir.getAbsolutePath()}/grobid-home/lib/lin-64/jep:" + - "${rootProject.rootDir.getAbsolutePath()}/grobid-home/lib/lin-64" + "${rootProject.rootDir.getAbsolutePath()}/grobid-home/lib/lin-64" } else { throw new RuntimeException("Unsupported platform!") } @@ -210,15 +210,22 @@ subprojects { if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { jvmArgs "--add-opens", "java.base/java.util.stream=ALL-UNNAMED", - "--add-opens", "java.base/java.io=ALL-UNNAMED", - "--add-opens", "java.xml/jdk.xml.internal=ALL-UNNAMED", - // PowerMock compatibility with Java 21 - TODO: Replace PowerMock with Mockito/JUnit Jupiter - "--add-opens", "java.base/java.lang=ALL-UNNAMED", - "--add-opens", "java.base/java.util=ALL-UNNAMED" + "--add-opens", "java.base/java.io=ALL-UNNAMED", + "--add-opens", "java.xml/jdk.xml.internal=ALL-UNNAMED", + // PowerMock compatibility with Java 21 - TODO: Replace PowerMock with Mockito/JUnit Jupiter + "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.util=ALL-UNNAMED" } - + systemProperty "java.library.path", "${javaLibraryPath}" } + + tasks.withType(Test).configureEach { + // Needed by some native libs (e.g. onnxruntime) under Java 17+ / 21 when + // accessing direct buffer internals. + jvmArgs '--add-opens=java.base/java.nio=ALL-UNNAMED', + '--add-opens=java.base/sun.nio.ch=ALL-UNNAMED' // Required for LMDB + } } /** SUBPROJECTS **/ @@ -259,6 +266,21 @@ project("grobid-core") { implementation 'org.apache.opennlp:opennlp-tools:1.9.4' implementation group: 'org.jruby', name: 'jruby-complete', version: '9.4.12.1' + // ONNX Runtime for model inference + // GPU version (onnxruntime_gpu) only supports Linux with NVIDIA CUDA + // CPU version (onnxruntime) supports all platforms including macOS ARM64 + // if (System.getProperty("os.name").toLowerCase().contains("linux")) { + // implementation 'com.microsoft.onnxruntime:onnxruntime_gpu:1.23.2' + // } else { + implementation 'com.microsoft.onnxruntime:onnxruntime:1.23.2' + // } + + // LMDB for word embeddings lookup (0.9.0+ includes Apple Silicon native libs) + implementation 'org.lmdbjava:lmdbjava:0.9.2' + + // JSON parsing (for CRF params and vocab) + implementation 'com.google.code.gson:gson:2.10.1' + shadedLib "org.apache.lucene:lucene-analyzers-common:4.5.1" } @@ -299,18 +321,18 @@ project("grobid-core") { processResources { filesMatching(["grobid-version.txt", "grobid-revision.txt"]) { expand( - project_version: project.property('version') ?: "unknown", - project_revision: rootProject.ext.gitRevision + project_version: project.property('version') ?: "unknown", + project_revision: rootProject.ext.gitRevision ) } } tasks.register( - "install", - { - dependsOn publishToMavenLocal - dependsOn 'shadowJar' - } + "install", + { + dependsOn publishToMavenLocal + dependsOn 'shadowJar' + } ) } @@ -336,8 +358,8 @@ project("grobid-home") { } } + import org.apache.tools.ant.taskdefs.condition.Os -import org.jetbrains.kotlin.gradle.tasks.KotlinCompile project(":grobid-service") { apply plugin: 'application' @@ -353,7 +375,9 @@ project(":grobid-service") { def javaLibraryPath = getJavaLibraryPath() if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { - jvmArgs "--add-opens", "java.base/java.lang=ALL-UNNAMED" + jvmArgs "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.nio=ALL-UNNAMED", // Required for LMDB + "--add-opens", "java.base/sun.nio.ch=ALL-UNNAMED" // Required for LMDB } workingDir = rootProject.rootDir @@ -490,32 +514,32 @@ project(":grobid-trainer") { } def trainerTasks = [ - "train_name_header" : "org.grobid.trainer.NameHeaderTrainer", - "train_name_citation" : "org.grobid.trainer.NameCitationTrainer", - "train_affiliation_address" : "org.grobid.trainer.AffiliationAddressTrainer", - "train_shorttext" : "org.grobid.trainer.ShorttextTrainer", - "train_figure" : "org.grobid.trainer.FigureTrainer", - "train_table" : "org.grobid.trainer.TableTrainer", - "train_citation" : "org.grobid.trainer.CitationTrainer", - "train_date" : "org.grobid.trainer.DateTrainer", - "train_reference_segmentation" : "org.grobid.trainer.ReferenceSegmenterTrainer", - "train_ebook_model" : "org.grobid.trainer.EbookTrainer", - "train_patent_citation" : "org.grobid.trainer.PatentParserTrainer", - "train_funding_acknowledgement": "org.grobid.trainer.FundingAcknowledgementTrainer" + "train_name_header" : "org.grobid.trainer.NameHeaderTrainer", + "train_name_citation" : "org.grobid.trainer.NameCitationTrainer", + "train_affiliation_address" : "org.grobid.trainer.AffiliationAddressTrainer", + "train_shorttext" : "org.grobid.trainer.ShorttextTrainer", + "train_figure" : "org.grobid.trainer.FigureTrainer", + "train_table" : "org.grobid.trainer.TableTrainer", + "train_citation" : "org.grobid.trainer.CitationTrainer", + "train_date" : "org.grobid.trainer.DateTrainer", + "train_reference_segmentation" : "org.grobid.trainer.ReferenceSegmenterTrainer", + "train_ebook_model" : "org.grobid.trainer.EbookTrainer", + "train_patent_citation" : "org.grobid.trainer.PatentParserTrainer", + "train_funding_acknowledgement": "org.grobid.trainer.FundingAcknowledgementTrainer" ] def complexTrainerTasks = [ - "train_header" : ["org.grobid.trainer.HeaderTrainer", ""], - "train_header_article_light" : ["org.grobid.trainer.HeaderTrainer", "article/light"], - "train_header_article_light_ref" : ["org.grobid.trainer.HeaderTrainer", "article/light-ref"], - "train_header_ietf" : ["org.grobid.trainer.HeaderTrainer", "sdo/ietf"], - "train_segmentation" : ["org.grobid.trainer.SegmentationTrainer", ""], - "train_segmentation_article_light" : ["org.grobid.trainer.SegmentationTrainer", "article/light"], - "train_segmentation_article_light_ref": ["org.grobid.trainer.SegmentationTrainer", "article/light-ref"], - "train_segmentation_ietf" : ["org.grobid.trainer.SegmentationTrainer", "sdo/ietf"], - "train_fulltext" : ["org.grobid.trainer.FulltextTrainer", ""], - "train_fulltext_article_light" : ["org.grobid.trainer.FulltextTrainer", "article/light"], - "train_fulltext_article_light_ref" : ["org.grobid.trainer.FulltextTrainer", "article/light-ref"], + "train_header" : ["org.grobid.trainer.HeaderTrainer", ""], + "train_header_article_light" : ["org.grobid.trainer.HeaderTrainer", "article/light"], + "train_header_article_light_ref" : ["org.grobid.trainer.HeaderTrainer", "article/light-ref"], + "train_header_ietf" : ["org.grobid.trainer.HeaderTrainer", "sdo/ietf"], + "train_segmentation" : ["org.grobid.trainer.SegmentationTrainer", ""], + "train_segmentation_article_light" : ["org.grobid.trainer.SegmentationTrainer", "article/light"], + "train_segmentation_article_light_ref": ["org.grobid.trainer.SegmentationTrainer", "article/light-ref"], + "train_segmentation_ietf" : ["org.grobid.trainer.SegmentationTrainer", "sdo/ietf"], + "train_fulltext" : ["org.grobid.trainer.FulltextTrainer", ""], + "train_fulltext_article_light" : ["org.grobid.trainer.FulltextTrainer", "article/light"], + "train_fulltext_article_light_ref" : ["org.grobid.trainer.FulltextTrainer", "article/light-ref"], ] def libraries = "" @@ -527,7 +551,7 @@ project(":grobid-trainer") { } } else if (Os.isFamily(Os.FAMILY_UNIX)) { libraries = "${file("../grobid-home/lib/lin-64/jep").absolutePath}:" + - "${file("../grobid-home/lib/lin-64").absolutePath}:" + "${file("../grobid-home/lib/lin-64").absolutePath}:" } else { throw new RuntimeException("Unsupported platform!") } @@ -577,12 +601,18 @@ project(":grobid-trainer") { classpath = sourceSets.main.runtimeClasspath args 'nlm', getArg('p2t', '.'), getArg('run', '0'), getArg('fileRatio', '1.0'), getArg('flavor', '') def javaLibraryPath = getJavaLibraryPath() + // Add additional lib paths for native libraries (LMDB) + def lmdbLibPath = Os.isFamily(Os.FAMILY_MAC) ? + ":/opt/homebrew/lib:/usr/local/lib" : + Os.isFamily(Os.FAMILY_UNIX) ? ":/usr/lib/x86_64-linux-gnu:/usr/lib64:/usr/local/lib" : "" if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { - jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED" + jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.nio=ALL-UNNAMED", // Required for LMDB + "--add-opens", "java.base/sun.nio.ch=ALL-UNNAMED" // Required for LMDB } else { jvmArgs '-Xmx3072m' } - systemProperty "java.library.path", "${javaLibraryPath}" + systemProperty "java.library.path", "${javaLibraryPath}${lmdbLibPath}" } task(teiEval, dependsOn: 'classes', type: JavaExec, group: 'modelevaluation') { @@ -590,13 +620,18 @@ project(":grobid-trainer") { classpath = sourceSets.main.runtimeClasspath args 'tei', getArg('p2t', '.'), getArg('run', '0'), getArg('fileRatio', '1.0'), getArg('flavor', '') def javaLibraryPath = getJavaLibraryPath() - + // Add additional lib paths for native libraries (LMDB) + def lmdbLibPath = Os.isFamily(Os.FAMILY_MAC) ? + ":/opt/homebrew/lib:/usr/local/lib" : + Os.isFamily(Os.FAMILY_UNIX) ? ":/usr/lib/x86_64-linux-gnu:/usr/lib64:/usr/local/lib" : "" if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { - jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED" + jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.nio=ALL-UNNAMED", // Required for LMDB + "--add-opens", "java.base/sun.nio.ch=ALL-UNNAMED" // Required for LMDB } else { jvmArgs '-Xmx3072m' } - systemProperty "java.library.path", "${javaLibraryPath}" + systemProperty "java.library.path", "${javaLibraryPath}${lmdbLibPath}" } task(PrepareDOIMatching, dependsOn: 'classes', type: JavaExec, group: 'modelevaluation') { @@ -604,14 +639,18 @@ project(":grobid-trainer") { classpath = sourceSets.main.runtimeClasspath args 'data', getArg('p2t', '.') def javaLibraryPath = getJavaLibraryPath() - + // Add additional lib paths for native libraries (LMDB) + def lmdbLibPath = Os.isFamily(Os.FAMILY_MAC) ? + ":/opt/homebrew/lib:/usr/local/lib" : + Os.isFamily(Os.FAMILY_UNIX) ? ":/usr/lib/x86_64-linux-gnu:/usr/lib64:/usr/local/lib" : "" if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { - jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED" + jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.nio=ALL-UNNAMED", // Required for LMDB + "--add-opens", "java.base/sun.nio.ch=ALL-UNNAMED" // Required for LMDB } else { jvmArgs '-Xmx3072m' } - - systemProperty "java.library.path", "${javaLibraryPath}" + systemProperty "java.library.path", "${javaLibraryPath}${lmdbLibPath}" } task(EvaluateDOIMatching, dependsOn: 'classes', type: JavaExec, group: 'modelevaluation') { @@ -620,14 +659,18 @@ project(":grobid-trainer") { args 'eval', getArg('p2t', '.') def javaLibraryPath = getJavaLibraryPath() - + // Add additional lib paths for native libraries (LMDB) + def lmdbLibPath = Os.isFamily(Os.FAMILY_MAC) ? + ":/opt/homebrew/lib:/usr/local/lib" : + Os.isFamily(Os.FAMILY_UNIX) ? ":/usr/lib/x86_64-linux-gnu:/usr/lib64:/usr/local/lib" : "" if (JavaVersion.current().compareTo(JavaVersion.VERSION_1_8) > 0) { - jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED" + jvmArgs '-Xmx3072m', "--add-opens", "java.base/java.lang=ALL-UNNAMED", + "--add-opens", "java.base/java.nio=ALL-UNNAMED", // Required for LMDB + "--add-opens", "java.base/sun.nio.ch=ALL-UNNAMED" // Required for LMDB } else { jvmArgs '-Xmx3072m' } - - systemProperty "java.library.path", "${javaLibraryPath}" + systemProperty "java.library.path", "${javaLibraryPath}${lmdbLibPath}" } } @@ -664,7 +707,7 @@ tasks.register("codeCoverageReport", JacocoReport) { /** COVERALLS **/ coveralls { - sourceDirs = files(subprojects.findAll { it.plugins.hasPlugin('java') }.sourceSets.main.allSource.srcDirs).files.absolutePath + sourceDirs = files(subprojects.findAll { it.plugins.hasPlugin('java') }.sourceSets.main.allSource.srcDirs).files.absolutePath } tasks.coveralls { diff --git a/doc/benchmarks/Benchmarking-biorxiv.md b/doc/benchmarks/Benchmarking-biorxiv.md index 8e60478dba..7dd67baa89 100644 --- a/doc/benchmarks/Benchmarking-biorxiv.md +++ b/doc/benchmarks/Benchmarking-biorxiv.md @@ -40,75 +40,75 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| abstract | 2.42 | 2.36 | 2.39 | 1990 | -| authors | 85.12 | 84.39 | 84.75 | 1999 | -| first_author | 96.92 | 96.19 | 96.56 | 1997 | -| keywords | 58.13 | 59.24 | 58.68 | 839 | -| title | 77.33 | 76.6 | 76.97 | 2000 | -| | | | | | -| **all fields (micro avg.)** | **65** | **64.41** | **64.7** | 8825 | -| all fields (macro avg.) | 63.98 | 63.76 | 63.87 | 8825 | - -#### Soft Matching (ignoring punctuation, case and space characters mismatches) - -**Field-level results** - | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 60.57 | 59.2 | 59.87 | 1990 | -| authors | 85.52 | 84.79 | 85.15 | 1999 | -| first_author | 97.12 | 96.39 | 96.76 | 1997 | -| keywords | 63.27 | 64.48 | 63.87 | 839 | -| title | 79.45 | 78.7 | 79.08 | 2000 | +| abstract | 2.26 | 2.21 | 2.24 | 1990 | +| authors | 84.13 | 83.54 | 83.84 | 1999 | +| first_author | 96.17 | 95.59 | 95.88 | 1997 | +| keywords | 49.6 | 51.61 | 50.58 | 839 | +| title | 76.04 | 75.55 | 75.8 | 2000 | | | | | | | -| **all fields (micro avg.)** | **79.05** | **78.33** | **78.69** | 8825 | -| all fields (macro avg.) | 77.19 | 76.71 | 76.95 | 8825 | +| **all fields (micro avg.)** | **63.44** | **63.08** | **63.26** | 8825 | +| all fields (macro avg.) | 61.64 | 61.7 | 61.67 | 8825 | -#### Levenshtein Matching (Minimum Levenshtein distance at 0.8) +#### Soft Matching (ignoring punctuation, case and space characters mismatches) **Field-level results** | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|----------|---------| -| abstract | 80.72 | 78.89 | 79.8 | 1990 | -| authors | 92.63 | 91.85 | 92.24 | 1999 | -| first_author | 97.38 | 96.64 | 97.01 | 1997 | -| keywords | 79.3 | 80.81 | 80.05 | 839 | -| title | 91.97 | 91.1 | 91.53 | 2000 | +| abstract | 57.63 | 56.33 | 56.98 | 1990 | +| authors | 84.53 | 83.94 | 84.24 | 1999 | +| first_author | 96.32 | 95.74 | 96.03 | 1997 | +| keywords | 54.07 | 56.26 | 55.14 | 839 | +| title | 78.41 | 77.9 | 78.15 | 2000 | | | | | | | -| **all fields (micro avg.)** | **89.61** | **88.79** | **89.2** | 8825 | -| all fields (macro avg.) | 88.4 | 87.86 | 88.13 | 8825 | +| **all fields (micro avg.)** | **76.82** | **76.39** | **76.6** | 8825 | +| all fields (macro avg.) | 74.19 | 74.03 | 74.11 | 8825 | -#### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) +#### Levenshtein Matching (Minimum Levenshtein distance at 0.8) **Field-level results** | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 77.22 | 75.48 | 76.34 | 1990 | -| authors | 88.7 | 87.94 | 88.32 | 1999 | -| first_author | 96.92 | 96.19 | 96.56 | 1997 | -| keywords | 70.99 | 72.35 | 71.66 | 839 | -| title | 87.63 | 86.8 | 87.21 | 2000 | +| abstract | 79.13 | 77.34 | 78.22 | 1990 | +| authors | 92.04 | 91.4 | 91.72 | 1999 | +| first_author | 96.62 | 96.04 | 96.33 | 1997 | +| keywords | 73.88 | 76.88 | 75.35 | 839 | +| title | 91.6 | 91 | 91.3 | 2000 | | | | | | | -| **all fields (micro avg.)** | **86.04** | **85.26** | **85.65** | 8825 | -| all fields (macro avg.) | 84.29 | 83.75 | 84.02 | 8825 | +| **all fields (micro avg.)** | **88.31** | **87.81** | **88.06** | 8825 | +| all fields (macro avg.) | 86.65 | 86.53 | 86.58 | 8825 | + +#### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) + +**Field-level results** + +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|--------|---------| +| abstract | 75.48 | 73.77 | 74.61 | 1990 | +| authors | 87.76 | 87.14 | 87.45 | 1999 | +| first_author | 96.17 | 95.59 | 95.88 | 1997 | +| keywords | 62.08 | 64.6 | 63.32 | 839 | +| title | 87.12 | 86.55 | 86.83 | 2000 | +| | | | | | +| **all fields (micro avg.)** | **84.24** | **83.76** | **84** | 8825 | +| all fields (macro avg.) | 81.72 | 81.53 | 81.62 | 8825 | #### Instance-level results ``` -Total expected instances: 2000 -Total correct instances: 40 (strict) -Total correct instances: 728 (soft) -Total correct instances: 1237 (Levenshtein) -Total correct instances: 1066 (ObservedRatcliffObershelp) - -Instance-level recall: 2 (strict) -Instance-level recall: 36.4 (soft) -Instance-level recall: 61.85 (Levenshtein) -Instance-level recall: 53.3 (RatcliffObershelp) +Total expected instances: 2000 +Total correct instances: 37 (strict) +Total correct instances: 641 (soft) +Total correct instances: 1176 (Levenshtein) +Total correct instances: 978 (ObservedRatcliffObershelp) + +Instance-level recall: 1.85 (strict) +Instance-level recall: 32.05 (soft) +Instance-level recall: 58.8 (Levenshtein) +Instance-level recall: 48.9 (RatcliffObershelp) ``` ## Citation metadata @@ -121,20 +121,20 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 88.2 | 83.12 | 85.58 | 97183 | -| date | 91.71 | 86.15 | 88.84 | 97630 | -| doi | 70.86 | 83.85 | 76.81 | 16894 | -| first_author | 95.08 | 89.53 | 92.22 | 97183 | -| inTitle | 82.9 | 79.31 | 81.06 | 96430 | -| issue | 94.35 | 91.93 | 93.13 | 30312 | -| page | 94.99 | 78.22 | 85.79 | 88597 | -| pmcid | 66.44 | 86.12 | 75.01 | 807 | -| pmid | 69.99 | 84.57 | 76.59 | 2093 | -| title | 84.9 | 83.42 | 84.16 | 92463 | -| volume | 96.27 | 95.07 | 95.66 | 87709 | +| authors | 87.25 | 81.11 | 84.07 | 97183 | +| date | 90.77 | 84.01 | 87.26 | 97630 | +| doi | 68.31 | 75.43 | 71.69 | 16894 | +| first_author | 94.26 | 87.54 | 90.78 | 97183 | +| inTitle | 82.48 | 78.11 | 80.23 | 96430 | +| issue | 92.34 | 84.86 | 88.44 | 30312 | +| page | 94.38 | 77.78 | 85.28 | 88597 | +| pmcid | 66.24 | 82.65 | 73.54 | 807 | +| pmid | 68.23 | 81.56 | 74.3 | 2093 | +| title | 84.61 | 82.04 | 83.3 | 92463 | +| volume | 95.36 | 93.56 | 94.45 | 87709 | | | | | | | -| **all fields (micro avg.)** | **89.87** | **85.21** | **87.48** | 707301 | -| all fields (macro avg.) | 85.06 | 85.57 | 84.99 | 707301 | +| **all fields (micro avg.)** | **89.09** | **83.26** | **86.08** | 707301 | +| all fields (macro avg.) | 84.02 | 82.6 | 83.03 | 707301 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -142,20 +142,20 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 89.35 | 84.21 | 86.71 | 97183 | -| date | 91.71 | 86.15 | 88.84 | 97630 | -| doi | 75.34 | 89.16 | 81.67 | 16894 | -| first_author | 95.51 | 89.93 | 92.64 | 97183 | -| inTitle | 92.37 | 88.38 | 90.33 | 96430 | -| issue | 94.35 | 91.93 | 93.13 | 30312 | -| page | 94.99 | 78.22 | 85.79 | 88597 | -| pmcid | 75.72 | 98.14 | 85.48 | 807 | -| pmid | 74.42 | 89.92 | 81.44 | 2093 | -| title | 93.25 | 91.63 | 92.43 | 92463 | -| volume | 96.27 | 95.07 | 95.66 | 87709 | +| authors | 88.39 | 82.17 | 85.16 | 97183 | +| date | 90.77 | 84.01 | 87.26 | 97630 | +| doi | 72.82 | 80.41 | 76.43 | 16894 | +| first_author | 94.67 | 87.92 | 91.17 | 97183 | +| inTitle | 91.9 | 87.03 | 89.4 | 96430 | +| issue | 92.34 | 84.86 | 88.44 | 30312 | +| page | 94.38 | 77.78 | 85.28 | 88597 | +| pmcid | 75.17 | 93.8 | 83.46 | 807 | +| pmid | 72.7 | 86.91 | 79.17 | 2093 | +| title | 92.89 | 90.07 | 91.46 | 92463 | +| volume | 95.36 | 93.56 | 94.45 | 87709 | | | | | | | -| **all fields (micro avg.)** | **92.69** | **87.88** | **90.22** | 707301 | -| all fields (macro avg.) | 88.48 | 89.34 | 88.56 | 707301 | +| **all fields (micro avg.)** | **91.88** | **85.87** | **88.78** | 707301 | +| all fields (macro avg.) | 87.4 | 86.23 | 86.52 | 707301 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -163,20 +163,20 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 94.61 | 89.16 | 91.81 | 97183 | -| date | 91.71 | 86.15 | 88.84 | 97630 | -| doi | 77.58 | 91.81 | 84.1 | 16894 | -| first_author | 95.66 | 90.08 | 92.78 | 97183 | -| inTitle | 93.36 | 89.32 | 91.29 | 96430 | -| issue | 94.35 | 91.93 | 93.13 | 30312 | -| page | 94.99 | 78.22 | 85.79 | 88597 | -| pmcid | 75.72 | 98.14 | 85.48 | 807 | -| pmid | 74.42 | 89.92 | 81.44 | 2093 | -| title | 96.08 | 94.41 | 95.24 | 92463 | -| volume | 96.27 | 95.07 | 95.66 | 87709 | +| authors | 93.71 | 87.12 | 90.29 | 97183 | +| date | 90.77 | 84.01 | 87.26 | 97630 | +| doi | 76.99 | 85.02 | 80.81 | 16894 | +| first_author | 94.82 | 88.06 | 91.31 | 97183 | +| inTitle | 92.84 | 87.92 | 90.31 | 96430 | +| issue | 92.34 | 84.86 | 88.44 | 30312 | +| page | 94.38 | 77.78 | 85.28 | 88597 | +| pmcid | 75.17 | 93.8 | 83.46 | 807 | +| pmid | 72.74 | 86.96 | 79.22 | 2093 | +| title | 95.79 | 92.88 | 94.31 | 92463 | +| volume | 95.36 | 93.56 | 94.45 | 87709 | | | | | | | -| **all fields (micro avg.)** | **94.01** | **89.14** | **91.51** | 707301 | -| all fields (macro avg.) | 89.52 | 90.38 | 89.6 | 707301 | +| **all fields (micro avg.)** | **93.27** | **87.17** | **90.12** | 707301 | +| all fields (macro avg.) | 88.63 | 87.45 | 87.74 | 707301 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -184,73 +184,73 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 91.57 | 86.3 | 88.85 | 97183 | -| date | 91.71 | 86.15 | 88.84 | 97630 | -| doi | 76.04 | 89.98 | 82.42 | 16894 | -| first_author | 95.13 | 89.58 | 92.27 | 97183 | -| inTitle | 91.13 | 87.19 | 89.11 | 96430 | -| issue | 94.35 | 91.93 | 93.13 | 30312 | -| page | 94.99 | 78.22 | 85.79 | 88597 | -| pmcid | 66.44 | 86.12 | 75.01 | 807 | -| pmid | 69.99 | 84.57 | 76.59 | 2093 | -| title | 95.41 | 93.75 | 94.57 | 92463 | -| volume | 96.27 | 95.07 | 95.66 | 87709 | +| authors | 90.59 | 84.22 | 87.29 | 97183 | +| date | 90.77 | 84.01 | 87.26 | 97630 | +| doi | 74.72 | 82.51 | 78.42 | 16894 | +| first_author | 94.3 | 87.58 | 90.82 | 97183 | +| inTitle | 90.71 | 85.9 | 88.24 | 96430 | +| issue | 92.34 | 84.86 | 88.44 | 30312 | +| page | 94.38 | 77.78 | 85.28 | 88597 | +| pmcid | 66.24 | 82.65 | 73.54 | 807 | +| pmid | 68.23 | 81.56 | 74.3 | 2093 | +| title | 95.12 | 92.24 | 93.66 | 92463 | +| volume | 95.36 | 93.56 | 94.45 | 87709 | | | | | | | -| **all fields (micro avg.)** | **93.05** | **88.22** | **90.57** | 707301 | -| all fields (macro avg.) | 87.55 | 88.08 | 87.48 | 707301 | +| **all fields (micro avg.)** | **92.3** | **86.26** | **89.18** | 707301 | +| all fields (macro avg.) | 86.62 | 85.17 | 85.61 | 707301 | #### Instance-level results ``` -Total expected instances: 98799 -Total extracted instances: 97808 -Total correct instances: 43695 (strict) -Total correct instances: 54689 (soft) -Total correct instances: 58863 (Levenshtein) -Total correct instances: 55597 (RatcliffObershelp) +Total expected instances: 98799 +Total extracted instances: 98373 +Total correct instances: 41161 (strict) +Total correct instances: 51566 (soft) +Total correct instances: 55887 (Levenshtein) +Total correct instances: 52758 (RatcliffObershelp) -Instance-level precision: 44.67 (strict) -Instance-level precision: 55.91 (soft) -Instance-level precision: 60.18 (Levenshtein) -Instance-level precision: 56.84 (RatcliffObershelp) +Instance-level precision: 41.84 (strict) +Instance-level precision: 52.42 (soft) +Instance-level precision: 56.81 (Levenshtein) +Instance-level precision: 53.63 (RatcliffObershelp) -Instance-level recall: 44.23 (strict) -Instance-level recall: 55.35 (soft) -Instance-level recall: 59.58 (Levenshtein) -Instance-level recall: 56.27 (RatcliffObershelp) +Instance-level recall: 41.66 (strict) +Instance-level recall: 52.19 (soft) +Instance-level recall: 56.57 (Levenshtein) +Instance-level recall: 53.4 (RatcliffObershelp) -Instance-level f-score: 44.45 (strict) -Instance-level f-score: 55.63 (soft) -Instance-level f-score: 59.88 (Levenshtein) -Instance-level f-score: 56.56 (RatcliffObershelp) +Instance-level f-score: 41.75 (strict) +Instance-level f-score: 52.31 (soft) +Instance-level f-score: 56.69 (Levenshtein) +Instance-level f-score: 53.51 (RatcliffObershelp) -Matching 1 : 79152 +Matching 1 : 77036 -Matching 2 : 4442 +Matching 2 : 4315 -Matching 3 : 4360 +Matching 3 : 4784 -Matching 4 : 2101 +Matching 4 : 2655 -Total matches : 90055 +Total matches : 88790 ``` #### Citation context resolution ``` -Total expected references: 98797 - 49.4 references per article -Total predicted references: 97808 - 48.9 references per article +Total expected references: 98797 - 49.4 references per article +Total predicted references: 98373 - 49.19 references per article -Total expected citation contexts: 142862 - 71.43 citation contexts per article -Total predicted citation contexts: 134498 - 67.25 citation contexts per article +Total expected citation contexts: 142862 - 71.43 citation contexts per article +Total predicted citation contexts: 132881 - 66.44 citation contexts per article -Total correct predicted citation contexts: 115971 - 57.99 citation contexts per article -Total wrong predicted citation contexts: 18527 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) +Total correct predicted citation contexts: 113221 - 56.61 citation contexts per article +Total wrong predicted citation contexts: 19660 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) -Precision citation contexts: 86.23 -Recall citation contexts: 81.18 -fscore citation contexts: 83.62 +Precision citation contexts: 85.2 +Recall citation contexts: 79.25 +fscore citation contexts: 82.12 ``` ## Fulltext structures @@ -268,17 +268,17 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 29.61 | 25.56 | 27.44 | 446 | -| figure_title | 4.29 | 2.34 | 3.03 | 22978 | -| funding_stmt | 3.46 | 22.95 | 6.01 | 745 | -| reference_citation | 72.02 | 70.94 | 71.48 | 147470 | -| reference_figure | 70.41 | 77.14 | 73.62 | 47984 | -| reference_table | 45.65 | 86.74 | 59.82 | 5957 | -| section_title | 71.35 | 69.91 | 70.62 | 32398 | +| availability_stmt | 29.05 | 25.34 | 27.07 | 446 | +| figure_title | 4.3 | 2.35 | 3.04 | 22978 | +| funding_stmt | 3.73 | 23.29 | 6.43 | 747 | +| reference_citation | 71.97 | 70.64 | 71.3 | 147470 | +| reference_figure | 70.38 | 77.13 | 73.6 | 47984 | +| reference_table | 45.62 | 86.64 | 59.76 | 5957 | +| section_title | 71.29 | 69.91 | 70.59 | 32398 | | table_title | 7.41 | 2.7 | 3.96 | 3925 | | | | | | | -| **all fields (micro avg.)** | **65.48** | **65.06** | **65.27** | 261903 | -| all fields (macro avg.) | 38.02 | 44.79 | 39.5 | 261903 | +| **all fields (micro avg.)** | **65.49** | **64.88** | **65.19** | 261905 | +| all fields (macro avg.) | 37.97 | 44.75 | 39.47 | 261905 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -286,26 +286,26 @@ Evaluation on 2000 random PDF files out of 1998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 50.65 | 43.72 | 46.93 | 446 | -| figure_title | 68.34 | 37.29 | 48.25 | 22978 | -| funding_stmt | 3.68 | 24.43 | 6.39 | 745 | -| reference_citation | 84.34 | 83.08 | 83.7 | 147470 | -| reference_figure | 71.05 | 77.84 | 74.29 | 47984 | -| reference_table | 46.07 | 87.53 | 60.36 | 5957 | -| section_title | 76.91 | 75.37 | 76.13 | 32398 | -| table_title | 82.8 | 30.17 | 44.22 | 3925 | +| availability_stmt | 49.87 | 43.5 | 46.47 | 446 | +| figure_title | 68.24 | 37.29 | 48.23 | 22978 | +| funding_stmt | 3.96 | 24.77 | 6.83 | 747 | +| reference_citation | 84.28 | 82.73 | 83.5 | 147470 | +| reference_figure | 71.02 | 77.83 | 74.27 | 47984 | +| reference_table | 46.03 | 87.43 | 60.31 | 5957 | +| section_title | 76.85 | 75.36 | 76.1 | 32398 | +| table_title | 82.73 | 30.14 | 44.18 | 3925 | | | | | | | -| **all fields (micro avg.)** | **76.72** | **76.22** | **76.47** | 261903 | -| all fields (macro avg.) | 60.48 | 57.43 | 55.04 | 261903 | +| **all fields (micro avg.)** | **76.73** | **76.02** | **76.38** | 261905 | +| all fields (macro avg.) | 60.37 | 57.38 | 54.99 | 261905 | **Document-level ratio results** | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 84.8 | 86.32 | 85.56 | 446 | +| availability_stmt | 84.2 | 87.22 | 85.68 | 446 | | | | | | | -| **all fields (micro avg.)** | **84.8** | **86.32** | **85.56** | 446 | -| all fields (macro avg.) | 84.8 | 86.32 | 85.56 | 446 | +| **all fields (micro avg.)** | **84.2** | **87.22** | **85.68** | 446 | +| all fields (macro avg.) | 84.2 | 87.22 | 85.68 | 446 | -Evaluation metrics produced in 1607.353 seconds +Evaluation metrics produced in 1598.033 seconds diff --git a/doc/benchmarks/Benchmarking-elife.md b/doc/benchmarks/Benchmarking-elife.md index da17249502..b5bf3e6376 100644 --- a/doc/benchmarks/Benchmarking-elife.md +++ b/doc/benchmarks/Benchmarking-elife.md @@ -41,13 +41,13 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 9.53 | 9.25 | 9.39 | 984 | -| authors | 74.79 | 73.96 | 74.37 | 983 | -| first_author | 92.59 | 91.65 | 92.12 | 982 | -| title | 86.93 | 85.16 | 86.04 | 984 | +| abstract | 9.56 | 9.25 | 9.4 | 984 | +| authors | 18.51 | 18.21 | 18.36 | 983 | +| first_author | 54.91 | 54.07 | 54.49 | 982 | +| title | 72.93 | 71.75 | 72.34 | 984 | | | | | | | -| **all fields (micro avg.)** | **66.17** | **64.99** | **65.57** | 3933 | -| all fields (macro avg.) | 65.96 | 65 | 65.48 | 3933 | +| **all fields (micro avg.)** | **39.1** | **38.32** | **38.71** | 3933 | +| all fields (macro avg.) | 38.98 | 38.32 | 38.65 | 3933 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -55,13 +55,13 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 22.3 | 21.65 | 21.97 | 984 | -| authors | 75.1 | 74.26 | 74.68 | 983 | -| first_author | 92.59 | 91.65 | 92.12 | 982 | -| title | 94.92 | 92.99 | 93.94 | 984 | +| abstract | 24.16 | 23.37 | 23.76 | 984 | +| authors | 18.82 | 18.51 | 18.67 | 983 | +| first_author | 54.91 | 54.07 | 54.49 | 982 | +| title | 81.3 | 79.98 | 80.64 | 984 | | | | | | | -| **all fields (micro avg.)** | **71.4** | **70.12** | **70.75** | 3933 | -| all fields (macro avg.) | 71.23 | 70.14 | 70.68 | 3933 | +| **all fields (micro avg.)** | **44.89** | **43.99** | **44.43** | 3933 | +| all fields (macro avg.) | 44.8 | 43.99 | 44.39 | 3933 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -69,13 +69,13 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 47.43 | 46.04 | 46.73 | 984 | -| authors | 88.68 | 87.69 | 88.18 | 983 | -| first_author | 92.9 | 91.96 | 92.43 | 982 | -| title | 96.37 | 94.41 | 95.38 | 984 | +| abstract | 48.63 | 47.05 | 47.83 | 984 | +| authors | 53.57 | 52.7 | 53.13 | 983 | +| first_author | 55.33 | 54.48 | 54.9 | 982 | +| title | 94.32 | 92.78 | 93.55 | 984 | | | | | | | -| **all fields (micro avg.)** | **81.47** | **80.02** | **80.73** | 3933 | -| all fields (macro avg.) | 81.35 | 80.02 | 80.68 | 3933 | +| **all fields (micro avg.)** | **63.03** | **61.76** | **62.39** | 3933 | +| all fields (macro avg.) | 62.96 | 61.75 | 62.35 | 3933 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -83,27 +83,27 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 44.5 | 43.19 | 43.84 | 984 | -| authors | 80.35 | 79.45 | 79.9 | 983 | -| first_author | 92.59 | 91.65 | 92.12 | 982 | -| title | 96.37 | 94.41 | 95.38 | 984 | +| abstract | 46.32 | 44.82 | 45.56 | 984 | +| authors | 29.27 | 28.79 | 29.03 | 983 | +| first_author | 54.91 | 54.07 | 54.49 | 982 | +| title | 90.39 | 88.92 | 89.65 | 984 | | | | | | | -| **all fields (micro avg.)** | **78.57** | **77.17** | **77.86** | 3933 | -| all fields (macro avg.) | 78.45 | 77.18 | 77.81 | 3933 | +| **all fields (micro avg.)** | **55.27** | **54.16** | **54.71** | 3933 | +| all fields (macro avg.) | 55.22 | 54.15 | 54.68 | 3933 | #### Instance-level results ``` -Total expected instances: 984 -Total correct instances: 74 (strict) -Total correct instances: 196 (soft) -Total correct instances: 381 (Levenshtein) -Total correct instances: 338 (ObservedRatcliffObershelp) - -Instance-level recall: 7.52 (strict) -Instance-level recall: 19.92 (soft) -Instance-level recall: 38.72 (Levenshtein) -Instance-level recall: 34.35 (RatcliffObershelp) +Total expected instances: 984 +Total correct instances: 9 (strict) +Total correct instances: 23 (soft) +Total correct instances: 119 (Levenshtein) +Total correct instances: 76 (ObservedRatcliffObershelp) + +Instance-level recall: 0.91 (strict) +Instance-level recall: 2.34 (soft) +Instance-level recall: 12.09 (Levenshtein) +Instance-level recall: 7.72 (RatcliffObershelp) ``` ## Citation metadata @@ -116,17 +116,17 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 79.43 | 78.36 | 78.89 | 63265 | -| date | 95.89 | 94.19 | 95.03 | 63662 | -| first_author | 94.83 | 93.51 | 94.17 | 63265 | -| inTitle | 95.82 | 94.87 | 95.34 | 63213 | -| issue | 2 | 75 | 3.9 | 16 | -| page | 96.28 | 95.44 | 95.86 | 53375 | -| title | 90.27 | 90.87 | 90.57 | 62044 | -| volume | 97.88 | 98.39 | 98.14 | 61049 | +| authors | 77.14 | 75.27 | 76.2 | 63265 | +| date | 94.9 | 91.62 | 93.23 | 63662 | +| first_author | 92.48 | 90.1 | 91.27 | 63265 | +| inTitle | 94.56 | 92.81 | 93.68 | 63213 | +| issue | 1.58 | 81.25 | 3.09 | 16 | +| page | 95.15 | 93.33 | 94.23 | 53375 | +| title | 89.52 | 88.7 | 89.11 | 62044 | +| volume | 97.08 | 96.22 | 96.65 | 61049 | | | | | | | -| **all fields (micro avg.)** | **92.7** | **92.13** | **92.42** | 429889 | -| all fields (macro avg.) | 81.55 | 90.08 | 81.49 | 429889 | +| **all fields (micro avg.)** | **91.28** | **89.61** | **90.43** | 429889 | +| all fields (macro avg.) | 80.3 | 88.66 | 79.68 | 429889 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -134,17 +134,17 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 79.57 | 78.49 | 79.03 | 63265 | -| date | 95.89 | 94.19 | 95.03 | 63662 | -| first_author | 94.91 | 93.59 | 94.25 | 63265 | -| inTitle | 96.29 | 95.35 | 95.82 | 63213 | -| issue | 2 | 75 | 3.9 | 16 | -| page | 96.28 | 95.44 | 95.86 | 53375 | -| title | 95.94 | 96.58 | 96.26 | 62044 | -| volume | 97.88 | 98.39 | 98.14 | 61049 | +| authors | 77.28 | 75.4 | 76.33 | 63265 | +| date | 94.9 | 91.62 | 93.23 | 63662 | +| first_author | 92.55 | 90.17 | 91.35 | 63265 | +| inTitle | 95.02 | 93.25 | 94.13 | 63213 | +| issue | 1.58 | 81.25 | 3.09 | 16 | +| page | 95.15 | 93.33 | 94.23 | 53375 | +| title | 95.17 | 94.3 | 94.73 | 62044 | +| volume | 97.08 | 96.22 | 96.65 | 61049 | | | | | | | -| **all fields (micro avg.)** | **93.63** | **93.06** | **93.34** | 429889 | -| all fields (macro avg.) | 82.35 | 90.88 | 82.28 | 429889 | +| **all fields (micro avg.)** | **92.2** | **90.51** | **91.35** | 429889 | +| all fields (macro avg.) | 81.09 | 89.44 | 80.47 | 429889 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -152,17 +152,17 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 93.33 | 92.07 | 92.7 | 63265 | -| date | 95.89 | 94.19 | 95.03 | 63662 | -| first_author | 95.36 | 94.03 | 94.69 | 63265 | -| inTitle | 96.62 | 95.67 | 96.14 | 63213 | -| issue | 2 | 75 | 3.9 | 16 | -| page | 96.28 | 95.44 | 95.86 | 53375 | -| title | 97.69 | 98.34 | 98.01 | 62044 | -| volume | 97.88 | 98.39 | 98.14 | 61049 | +| authors | 91.16 | 88.94 | 90.04 | 63265 | +| date | 94.9 | 91.62 | 93.23 | 63662 | +| first_author | 92.98 | 90.59 | 91.77 | 63265 | +| inTitle | 95.35 | 93.58 | 94.46 | 63213 | +| issue | 1.58 | 81.25 | 3.09 | 16 | +| page | 95.15 | 93.33 | 94.23 | 53375 | +| title | 97.34 | 96.45 | 96.89 | 62044 | +| volume | 97.08 | 96.22 | 96.65 | 61049 | | | | | | | -| **all fields (micro avg.)** | **96.01** | **95.42** | **95.71** | 429889 | -| all fields (macro avg.) | 84.38 | 92.89 | 84.31 | 429889 | +| **all fields (micro avg.)** | **94.65** | **92.92** | **93.78** | 429889 | +| all fields (macro avg.) | 83.19 | 91.5 | 82.54 | 429889 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -170,70 +170,70 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 86.75 | 85.57 | 86.16 | 63265 | -| date | 95.89 | 94.19 | 95.03 | 63662 | -| first_author | 94.84 | 93.53 | 94.18 | 63265 | -| inTitle | 96.3 | 95.35 | 95.82 | 63213 | -| issue | 2 | 75 | 3.9 | 16 | -| page | 96.28 | 95.44 | 95.86 | 53375 | -| title | 97.54 | 98.18 | 97.86 | 62044 | -| volume | 97.88 | 98.39 | 98.14 | 61049 | +| authors | 84.33 | 82.28 | 83.29 | 63265 | +| date | 94.9 | 91.62 | 93.23 | 63662 | +| first_author | 92.49 | 90.11 | 91.29 | 63265 | +| inTitle | 95.04 | 93.28 | 94.15 | 63213 | +| issue | 1.58 | 81.25 | 3.09 | 16 | +| page | 95.15 | 93.33 | 94.23 | 53375 | +| title | 97.08 | 96.19 | 96.63 | 62044 | +| volume | 97.08 | 96.22 | 96.65 | 61049 | | | | | | | -| **all fields (micro avg.)** | **94.9** | **94.32** | **94.61** | 429889 | -| all fields (macro avg.) | 83.43 | 91.96 | 83.37 | 429889 | +| **all fields (micro avg.)** | **93.5** | **91.79** | **92.64** | 429889 | +| all fields (macro avg.) | 82.2 | 90.53 | 81.57 | 429889 | #### Instance-level results ``` -Total expected instances: 63664 -Total extracted instances: 66152 -Total correct instances: 42401 (strict) -Total correct instances: 45243 (soft) -Total correct instances: 52907 (Levenshtein) -Total correct instances: 49502 (RatcliffObershelp) +Total expected instances: 63664 +Total extracted instances: 68032 +Total correct instances: 40158 (strict) +Total correct instances: 42810 (soft) +Total correct instances: 50131 (Levenshtein) +Total correct instances: 46885 (RatcliffObershelp) -Instance-level precision: 64.1 (strict) -Instance-level precision: 68.39 (soft) -Instance-level precision: 79.98 (Levenshtein) -Instance-level precision: 74.83 (RatcliffObershelp) +Instance-level precision: 59.03 (strict) +Instance-level precision: 62.93 (soft) +Instance-level precision: 73.69 (Levenshtein) +Instance-level precision: 68.92 (RatcliffObershelp) -Instance-level recall: 66.6 (strict) -Instance-level recall: 71.07 (soft) -Instance-level recall: 83.1 (Levenshtein) -Instance-level recall: 77.76 (RatcliffObershelp) +Instance-level recall: 63.08 (strict) +Instance-level recall: 67.24 (soft) +Instance-level recall: 78.74 (Levenshtein) +Instance-level recall: 73.64 (RatcliffObershelp) -Instance-level f-score: 65.32 (strict) -Instance-level f-score: 69.7 (soft) -Instance-level f-score: 81.51 (Levenshtein) -Instance-level f-score: 76.26 (RatcliffObershelp) +Instance-level f-score: 60.99 (strict) +Instance-level f-score: 65.01 (soft) +Instance-level f-score: 76.13 (Levenshtein) +Instance-level f-score: 71.2 (RatcliffObershelp) -Matching 1 : 58715 +Matching 1 : 57007 -Matching 2 : 1019 +Matching 2 : 1057 -Matching 3 : 1252 +Matching 3 : 1499 -Matching 4 : 368 +Matching 4 : 731 -Total matches : 61354 +Total matches : 60294 ``` #### Citation context resolution ``` -Total expected references: 63664 - 64.7 references per article -Total predicted references: 66152 - 67.23 references per article +Total expected references: 63664 - 64.7 references per article +Total predicted references: 68032 - 69.14 references per article -Total expected citation contexts: 109022 - 110.79 citation contexts per article -Total predicted citation contexts: 99982 - 101.61 citation contexts per article +Total expected citation contexts: 109022 - 110.79 citation contexts per article +Total predicted citation contexts: 98768 - 100.37 citation contexts per article -Total correct predicted citation contexts: 96212 - 97.78 citation contexts per article -Total wrong predicted citation contexts: 3770 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) +Total correct predicted citation contexts: 93697 - 95.22 citation contexts per article +Total wrong predicted citation contexts: 5071 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) -Precision citation contexts: 96.23 -Recall citation contexts: 88.25 -fscore citation contexts: 92.07 +Precision citation contexts: 94.87 +Recall citation contexts: 85.94 +fscore citation contexts: 90.18 ``` ## Fulltext structures @@ -251,43 +251,43 @@ Evaluation on 984 random PDF files out of 982 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 29.21 | 27.86 | 28.52 | 585 | +| availability_stmt | 29.11 | 27.86 | 28.47 | 585 | | figure_title | 0.07 | 0.02 | 0.03 | 31718 | -| funding_stmt | 6.18 | 29.53 | 10.22 | 921 | -| reference_citation | 57.06 | 55.97 | 56.51 | 108949 | -| reference_figure | 58.42 | 51.02 | 54.47 | 68926 | -| reference_table | 71.83 | 73.46 | 72.63 | 2381 | -| section_title | 82.81 | 77.25 | 79.93 | 21831 | +| funding_stmt | 7.11 | 23.45 | 10.91 | 921 | +| reference_citation | 56.96 | 55.81 | 56.38 | 108949 | +| reference_figure | 58.41 | 51.02 | 54.46 | 68926 | +| reference_table | 71.71 | 73.46 | 72.57 | 2381 | +| section_title | 82.82 | 77.27 | 79.95 | 21831 | | table_title | 0 | 0 | 0 | 1925 | | | | | | | -| **all fields (micro avg.)** | **56.03** | **48.56** | **52.03** | 237236 | -| all fields (macro avg.) | 38.2 | 39.39 | 37.79 | 237236 | +| **all fields (micro avg.)** | **56.3** | **48.46** | **52.09** | 237236 | +| all fields (macro avg.) | 38.27 | 38.61 | 37.85 | 237236 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| availability_stmt | 40.68 | 38.8 | 39.72 | 585 | -| figure_title | 49.75 | 16 | 24.21 | 31718 | -| funding_stmt | 6.18 | 29.53 | 10.22 | 921 | -| reference_citation | 93.6 | 91.81 | 92.7 | 108949 | -| reference_figure | 58.71 | 51.27 | 54.73 | 68926 | -| reference_table | 71.91 | 73.54 | 72.72 | 2381 | -| section_title | 83.85 | 78.21 | 80.93 | 21831 | -| table_title | 94.26 | 28.16 | 43.36 | 1925 | -| | | | | | -| **all fields (micro avg.)** | **77.97** | **67.57** | **72.4** | 237236 | -| all fields (macro avg.) | 62.37 | 50.92 | 52.32 | 237236 | - -**Document-level ratio results** - | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 96.88 | 95.38 | 96.12 | 585 | +| availability_stmt | 40 | 38.29 | 39.13 | 585 | +| figure_title | 49.52 | 16.04 | 24.24 | 31718 | +| funding_stmt | 7.11 | 23.45 | 10.91 | 921 | +| reference_citation | 93.51 | 91.61 | 92.55 | 108949 | +| reference_figure | 58.69 | 51.27 | 54.73 | 68926 | +| reference_table | 71.83 | 73.58 | 72.7 | 2381 | +| section_title | 83.86 | 78.23 | 80.95 | 21831 | +| table_title | 94.25 | 28.1 | 43.3 | 1925 | | | | | | | -| **all fields (micro avg.)** | **96.88** | **95.38** | **96.12** | 585 | -| all fields (macro avg.) | 96.88 | 95.38 | 96.12 | 585 | +| **all fields (micro avg.)** | **78.38** | **67.46** | **72.51** | 237236 | +| all fields (macro avg.) | 62.35 | 50.07 | 52.31 | 237236 | + +**Document-level ratio results** + +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|----------|---------| +| availability_stmt | 96.89 | 95.73 | 96.3 | 585 | +| | | | | | +| **all fields (micro avg.)** | **96.89** | **95.73** | **96.3** | 585 | +| all fields (macro avg.) | 96.89 | 95.73 | 96.3 | 585 | -Evaluation metrics produced in 1348.778 seconds +Evaluation metrics produced in 1353.877 seconds diff --git a/doc/benchmarks/Benchmarking-plos.md b/doc/benchmarks/Benchmarking-plos.md index 0bd2c68a3e..e6601603e6 100644 --- a/doc/benchmarks/Benchmarking-plos.md +++ b/doc/benchmarks/Benchmarking-plos.md @@ -41,44 +41,44 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 13.33 | 13.33 | 13.33 | 960 | -| authors | 99.07 | 99.07 | 99.07 | 969 | -| first_author | 99.28 | 99.28 | 99.28 | 969 | +| abstract | 12.53 | 12.81 | 12.67 | 960 | +| authors | 50.77 | 50.77 | 50.77 | 969 | +| first_author | 82.77 | 82.77 | 82.77 | 969 | | keywords | 0 | 0 | 0 | 0 | -| title | 95.97 | 95.3 | 95.63 | 1000 | +| title | 67.14 | 66.8 | 66.97 | 1000 | | | | | | | -| **all fields (micro avg.)** | **77.18** | **77.04** | **77.11** | 3898 | -| all fields (macro avg.) | 76.91 | 76.75 | 76.83 | 3898 | +| **all fields (micro avg.)** | **53.26** | **53.49** | **53.37** | 3898 | +| all fields (macro avg.) | 53.3 | 53.29 | 53.29 | 3898 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| abstract | 50.52 | 50.52 | 50.52 | 960 | -| authors | 99.07 | 99.07 | 99.07 | 969 | -| first_author | 99.28 | 99.28 | 99.28 | 969 | -| keywords | 0 | 0 | 0 | 0 | -| title | 99.6 | 98.9 | 99.25 | 1000 | -| | | | | | -| **all fields (micro avg.)** | **87.28** | **87.12** | **87.2** | 3898 | -| all fields (macro avg.) | 87.12 | 86.94 | 87.03 | 3898 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| abstract | 46.33 | 47.4 | 46.86 | 960 | +| authors | 52.32 | 52.32 | 52.32 | 969 | +| first_author | 82.97 | 82.97 | 82.97 | 969 | +| keywords | 0 | 0 | 0 | 0 | +| title | 81.51 | 81.1 | 81.3 | 1000 | +| | | | | | +| **all fields (micro avg.)** | **65.82** | **66.11** | **65.97** | 3898 | +| all fields (macro avg.) | 65.78 | 65.95 | 65.86 | 3898 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| abstract | 76.67 | 76.67 | 76.67 | 960 | -| authors | 99.48 | 99.48 | 99.48 | 969 | -| first_author | 99.38 | 99.38 | 99.38 | 969 | -| keywords | 0 | 0 | 0 | 0 | -| title | 99.7 | 99 | 99.35 | 1000 | -| | | | | | -| **all fields (micro avg.)** | **93.88** | **93.71** | **93.8** | 3898 | -| all fields (macro avg.) | 93.81 | 93.63 | 93.72 | 3898 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| abstract | 70.37 | 71.98 | 71.16 | 960 | +| authors | 81.01 | 81.01 | 81.01 | 969 | +| first_author | 84.42 | 84.42 | 84.42 | 969 | +| keywords | 0 | 0 | 0 | 0 | +| title | 97.39 | 96.9 | 97.14 | 1000 | +| | | | | | +| **all fields (micro avg.)** | **83.35** | **83.71** | **83.53** | 3898 | +| all fields (macro avg.) | 83.3 | 83.58 | 83.43 | 3898 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -86,28 +86,28 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 66.56 | 66.56 | 66.56 | 960 | -| authors | 99.38 | 99.38 | 99.38 | 969 | -| first_author | 99.28 | 99.28 | 99.28 | 969 | +| abstract | 62.22 | 63.65 | 62.92 | 960 | +| authors | 62.33 | 62.33 | 62.33 | 969 | +| first_author | 82.87 | 82.87 | 82.87 | 969 | | keywords | 0 | 0 | 0 | 0 | -| title | 99.7 | 99 | 99.35 | 1000 | +| title | 92.66 | 92.2 | 92.43 | 1000 | | | | | | | -| **all fields (micro avg.)** | **91.34** | **91.17** | **91.26** | 3898 | -| all fields (macro avg.) | 91.23 | 91.06 | 91.14 | 3898 | +| **all fields (micro avg.)** | **75.1** | **75.42** | **75.26** | 3898 | +| all fields (macro avg.) | 75.02 | 75.26 | 75.14 | 3898 | #### Instance-level results ``` -Total expected instances: 1000 -Total correct instances: 142 (strict) -Total correct instances: 491 (soft) -Total correct instances: 729 (Levenshtein) -Total correct instances: 641 (ObservedRatcliffObershelp) - -Instance-level recall: 14.2 (strict) -Instance-level recall: 49.1 (soft) -Instance-level recall: 72.9 (Levenshtein) -Instance-level recall: 64.1 (RatcliffObershelp) +Total expected instances: 1000 +Total correct instances: 58 (strict) +Total correct instances: 227 (soft) +Total correct instances: 504 (Levenshtein) +Total correct instances: 365 (ObservedRatcliffObershelp) + +Instance-level recall: 5.8 (strict) +Instance-level recall: 22.7 (soft) +Instance-level recall: 50.4 (Levenshtein) +Instance-level recall: 36.5 (RatcliffObershelp) ``` ## Citation metadata @@ -120,17 +120,17 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 81.18 | 78.43 | 79.78 | 44770 | -| date | 84.64 | 81.25 | 82.91 | 45457 | -| first_author | 91.49 | 88.36 | 89.9 | 44770 | -| inTitle | 81.69 | 83.58 | 82.62 | 42795 | -| issue | 93.63 | 92.71 | 93.17 | 18983 | -| page | 93.72 | 77.57 | 84.88 | 40844 | -| title | 59.97 | 60.48 | 60.23 | 43101 | -| volume | 95.91 | 96.12 | 96.02 | 40458 | +| authors | 81.1 | 77.96 | 79.49 | 44770 | +| date | 84.27 | 80.33 | 82.25 | 45457 | +| first_author | 91.33 | 87.77 | 89.51 | 44770 | +| inTitle | 81.71 | 83.51 | 82.6 | 42795 | +| issue | 91.98 | 89.6 | 90.77 | 18983 | +| page | 93.59 | 77.77 | 84.95 | 40844 | +| title | 59.92 | 59.92 | 59.92 | 43101 | +| volume | 94.88 | 95.2 | 95.04 | 40458 | | | | | | | -| **all fields (micro avg.)** | **84.25** | **81.46** | **82.83** | 321178 | -| all fields (macro avg.) | 85.28 | 82.31 | 83.69 | 321178 | +| **all fields (micro avg.)** | **83.93** | **80.82** | **82.35** | 321178 | +| all fields (macro avg.) | 84.85 | 81.51 | 83.07 | 321178 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -138,17 +138,17 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 81.5 | 78.74 | 80.09 | 44770 | -| date | 84.64 | 81.25 | 82.91 | 45457 | -| first_author | 91.71 | 88.57 | 90.11 | 44770 | -| inTitle | 85.52 | 87.51 | 86.5 | 42795 | -| issue | 93.63 | 92.71 | 93.17 | 18983 | -| page | 93.72 | 77.57 | 84.88 | 40844 | -| title | 91.98 | 92.75 | 92.37 | 43101 | -| volume | 95.91 | 96.12 | 96.02 | 40458 | +| authors | 81.43 | 78.28 | 79.83 | 44770 | +| date | 84.27 | 80.33 | 82.25 | 45457 | +| first_author | 91.56 | 87.99 | 89.74 | 44770 | +| inTitle | 85.55 | 87.44 | 86.48 | 42795 | +| issue | 91.98 | 89.6 | 90.77 | 18983 | +| page | 93.59 | 77.77 | 84.95 | 40844 | +| title | 91.97 | 91.96 | 91.96 | 43101 | +| volume | 94.88 | 95.2 | 95.04 | 40458 | | | | | | | -| **all fields (micro avg.)** | **89.34** | **86.38** | **87.84** | 321178 | -| all fields (macro avg.) | 89.83 | 86.9 | 88.26 | 321178 | +| **all fields (micro avg.)** | **89.02** | **85.72** | **87.34** | 321178 | +| all fields (macro avg.) | 89.4 | 86.07 | 87.63 | 321178 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -156,88 +156,88 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 90.66 | 87.59 | 89.09 | 44770 | -| date | 84.64 | 81.25 | 82.91 | 45457 | -| first_author | 92.25 | 89.09 | 90.64 | 44770 | -| inTitle | 86.46 | 88.48 | 87.46 | 42795 | -| issue | 93.63 | 92.71 | 93.17 | 18983 | -| page | 93.72 | 77.57 | 84.88 | 40844 | -| title | 94.58 | 95.38 | 94.98 | 43101 | -| volume | 95.91 | 96.12 | 96.02 | 40458 | +| authors | 90.55 | 87.04 | 88.76 | 44770 | +| date | 84.27 | 80.33 | 82.25 | 45457 | +| first_author | 92.09 | 88.5 | 90.26 | 44770 | +| inTitle | 86.33 | 88.23 | 87.27 | 42795 | +| issue | 91.98 | 89.6 | 90.77 | 18983 | +| page | 93.59 | 77.77 | 84.95 | 40844 | +| title | 94.58 | 94.58 | 94.58 | 43101 | +| volume | 94.88 | 95.2 | 95.04 | 40458 | | | | | | | -| **all fields (micro avg.)** | **91.19** | **88.17** | **89.65** | 321178 | -| all fields (macro avg.) | 91.48 | 88.52 | 89.89 | 321178 | +| **all fields (micro avg.)** | **90.84** | **87.47** | **89.12** | 321178 | +| all fields (macro avg.) | 91.03 | 87.66 | 89.24 | 321178 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| authors | 84.94 | 82.07 | 83.48 | 44770 | -| date | 84.64 | 81.25 | 82.91 | 45457 | -| first_author | 91.49 | 88.36 | 89.9 | 44770 | -| inTitle | 85.17 | 87.15 | 86.15 | 42795 | -| issue | 93.63 | 92.71 | 93.17 | 18983 | -| page | 93.72 | 77.57 | 84.88 | 40844 | -| title | 93.97 | 94.76 | 94.36 | 43101 | -| volume | 95.91 | 96.12 | 96.02 | 40458 | -| | | | | | -| **all fields (micro avg.)** | **90.02** | **87.04** | **88.5** | 321178 | -| all fields (macro avg.) | 90.43 | 87.5 | 88.86 | 321178 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| authors | 84.87 | 81.59 | 83.2 | 44770 | +| date | 84.27 | 80.33 | 82.25 | 45457 | +| first_author | 91.33 | 87.77 | 89.51 | 44770 | +| inTitle | 85.17 | 87.05 | 86.1 | 42795 | +| issue | 91.98 | 89.6 | 90.77 | 18983 | +| page | 93.59 | 77.77 | 84.95 | 40844 | +| title | 93.9 | 93.9 | 93.9 | 43101 | +| volume | 94.88 | 95.2 | 95.04 | 40458 | +| | | | | | +| **all fields (micro avg.)** | **89.68** | **86.35** | **87.99** | 321178 | +| all fields (macro avg.) | 90 | 86.65 | 88.22 | 321178 | #### Instance-level results ``` -Total expected instances: 48449 -Total extracted instances: 48221 -Total correct instances: 13495 (strict) -Total correct instances: 22265 (soft) -Total correct instances: 24914 (Levenshtein) -Total correct instances: 23267 (RatcliffObershelp) +Total expected instances: 48449 +Total extracted instances: 48947 +Total correct instances: 13305 (strict) +Total correct instances: 21985 (soft) +Total correct instances: 24553 (Levenshtein) +Total correct instances: 22959 (RatcliffObershelp) -Instance-level precision: 27.99 (strict) -Instance-level precision: 46.17 (soft) -Instance-level precision: 51.67 (Levenshtein) -Instance-level precision: 48.25 (RatcliffObershelp) +Instance-level precision: 27.18 (strict) +Instance-level precision: 44.92 (soft) +Instance-level precision: 50.16 (Levenshtein) +Instance-level precision: 46.91 (RatcliffObershelp) -Instance-level recall: 27.85 (strict) -Instance-level recall: 45.96 (soft) -Instance-level recall: 51.42 (Levenshtein) -Instance-level recall: 48.02 (RatcliffObershelp) +Instance-level recall: 27.46 (strict) +Instance-level recall: 45.38 (soft) +Instance-level recall: 50.68 (Levenshtein) +Instance-level recall: 47.39 (RatcliffObershelp) -Instance-level f-score: 27.92 (strict) -Instance-level f-score: 46.06 (soft) -Instance-level f-score: 51.54 (Levenshtein) -Instance-level f-score: 48.14 (RatcliffObershelp) +Instance-level f-score: 27.32 (strict) +Instance-level f-score: 45.15 (soft) +Instance-level f-score: 50.42 (Levenshtein) +Instance-level f-score: 47.15 (RatcliffObershelp) -Matching 1 : 35376 +Matching 1 : 34852 -Matching 2 : 1259 +Matching 2 : 1274 -Matching 3 : 3266 +Matching 3 : 3388 -Matching 4 : 1799 +Matching 4 : 2026 -Total matches : 41700 +Total matches : 41540 ``` #### Citation context resolution ``` -Total expected references: 48449 - 48.45 references per article -Total predicted references: 48221 - 48.22 references per article +Total expected references: 48449 - 48.45 references per article +Total predicted references: 48947 - 48.95 references per article -Total expected citation contexts: 69755 - 69.75 citation contexts per article -Total predicted citation contexts: 73164 - 73.16 citation contexts per article +Total expected citation contexts: 69755 - 69.75 citation contexts per article +Total predicted citation contexts: 71896 - 71.9 citation contexts per article -Total correct predicted citation contexts: 56709 - 56.71 citation contexts per article -Total wrong predicted citation contexts: 16455 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) +Total correct predicted citation contexts: 55389 - 55.39 citation contexts per article +Total wrong predicted citation contexts: 16507 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) -Precision citation contexts: 77.51 -Recall citation contexts: 81.3 -fscore citation contexts: 79.36 +Precision citation contexts: 77.04 +Recall citation contexts: 79.41 +fscore citation contexts: 78.2 ``` ## Fulltext structures @@ -253,47 +253,46 @@ Evaluation on 1000 random PDF files out of 998 PDF (ratio 1.0). **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|-----------|---------| -| availability_stmt | 54 | 51.99 | 52.98 | 779 | -| figure_title | 0.2 | 0.1 | 0.13 | 8943 | -| funding_stmt | 5.47 | 30.72 | 9.28 | 1507 | -| reference_citation | 87.96 | 94.35 | 91.04 | 69741 | -| reference_figure | 74.18 | 85.72 | 79.53 | 11010 | -| reference_table | 70.28 | 94.3 | 80.54 | 5159 | -| section_title | 72.63 | 66.19 | 69.26 | 17540 | -| table_title | 0 | 0 | 0 | 6092 | -| | | | | | -| **all fields (micro avg.)** | **74.06** | **76.67** | **75.34** | 120771 | -| all fields (macro avg.) | 45.59 | 52.92 | 47.85 | 120771 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|----------|----------|---------| +| availability_stmt | 46.79 | 44.93 | 45.84 | 779 | +| figure_title | 0.22 | 0.11 | 0.15 | 8943 | +| funding_stmt | 5.77 | 26.74 | 9.49 | 1507 | +| reference_citation | 87.92 | 94.06 | 90.89 | 69741 | +| reference_figure | 74.2 | 85.74 | 79.55 | 11010 | +| reference_table | 70.27 | 94.28 | 80.52 | 5159 | +| section_title | 72.65 | 66.18 | 69.27 | 17540 | +| table_title | 0.12 | 0.02 | 0.03 | 6092 | +| | | | | | +| **all fields (micro avg.)** | **74.82** | **76.4** | **75.6** | 120771 | +| all fields (macro avg.) | 44.74 | 51.51 | 46.97 | 120771 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|----------|-----------|---------| -| availability_stmt | 79.73 | 76.77 | 78.22 | 779 | -| figure_title | 90.96 | 45.79 | 60.91 | 8943 | -| funding_stmt | 6.99 | 39.28 | 11.87 | 1507 | -| reference_citation | 87.96 | 94.36 | 91.05 | 69741 | -| reference_figure | 74.42 | 86 | 79.8 | 11010 | -| reference_table | 70.44 | 94.51 | 80.72 | 5159 | -| section_title | 78.4 | 71.45 | 74.76 | 17540 | -| table_title | 53.33 | 7.5 | 13.15 | 6092 | -| | | | | | -| **all fields (micro avg.)** | **78.73** | **81.5** | **80.09** | 120771 | -| all fields (macro avg.) | 67.78 | 64.46 | 61.31 | 120771 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| availability_stmt | 68.58 | 65.85 | 67.19 | 779 | +| figure_title | 90.88 | 45.78 | 60.89 | 8943 | +| funding_stmt | 7.26 | 33.64 | 11.94 | 1507 | +| reference_citation | 87.93 | 94.06 | 90.89 | 69741 | +| reference_figure | 74.44 | 86.02 | 79.81 | 11010 | +| reference_table | 70.43 | 94.5 | 80.71 | 5159 | +| section_title | 78.43 | 71.44 | 74.77 | 17540 | +| table_title | 53.5 | 7.52 | 13.18 | 6092 | +| | | | | | +| **all fields (micro avg.)** | **79.51** | **81.19** | **80.34** | 120771 | +| all fields (macro avg.) | 66.43 | 62.35 | 59.92 | 120771 | **Document-level ratio results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|-----------|----------|---------| -| availability_stmt | 100 | 96.28 | 98.1 | 779 | -| | | | | | -| **all fields (micro avg.)** | **100** | **96.28** | **98.1** | 779 | -| all fields (macro avg.) | 100 | 96.28 | 98.1 | 779 | - -Evaluation metrics produced in 795.257 seconds +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| availability_stmt | 99.6 | 96.02 | 97.78 | 779 | +| | | | | | +| **all fields (micro avg.)** | **99.6** | **96.02** | **97.78** | 779 | +| all fields (macro avg.) | 99.6 | 96.02 | 97.78 | 779 | +Evaluation metrics produced in 777.894 seconds diff --git a/doc/benchmarks/Benchmarking-pmc.md b/doc/benchmarks/Benchmarking-pmc.md index 4f428bd1bc..cbf044c891 100644 --- a/doc/benchmarks/Benchmarking-pmc.md +++ b/doc/benchmarks/Benchmarking-pmc.md @@ -41,14 +41,14 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 16.89 | 16.54 | 16.71 | 1911 | -| authors | 92.78 | 92.63 | 92.7 | 1941 | -| first_author | 96.8 | 96.65 | 96.73 | 1941 | -| keywords | 65.58 | 63.91 | 64.73 | 1380 | -| title | 84.46 | 84.2 | 84.33 | 1943 | +| abstract | 16.21 | 15.91 | 16.06 | 1911 | +| authors | 61.02 | 60.74 | 60.88 | 1941 | +| first_author | 88.51 | 88.1 | 88.3 | 1941 | +| keywords | 46.36 | 40.14 | 43.03 | 1380 | +| title | 70.06 | 69.12 | 69.59 | 1943 | | | | | | | -| **all fields (micro avg.)** | **72.08** | **71.39** | **71.73** | 9116 | -| all fields (macro avg.) | 71.3 | 70.79 | 71.04 | 9116 | +| **all fields (micro avg.)** | **57.51** | **55.84** | **56.66** | 9116 | +| all fields (macro avg.) | 56.43 | 54.8 | 55.57 | 9116 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -56,14 +56,14 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 63.98 | 62.64 | 63.3 | 1911 | -| authors | 94.74 | 94.59 | 94.66 | 1941 | -| first_author | 97.21 | 97.06 | 97.14 | 1941 | -| keywords | 74.2 | 72.32 | 73.25 | 1380 | -| title | 92 | 91.71 | 91.86 | 1943 | +| abstract | 59.25 | 58.14 | 58.69 | 1911 | +| authors | 61.23 | 60.95 | 61.09 | 1941 | +| first_author | 88.61 | 88.2 | 88.41 | 1941 | +| keywords | 53.72 | 46.52 | 49.86 | 1380 | +| title | 77.99 | 76.94 | 77.46 | 1943 | | | | | | | -| **all fields (micro avg.)** | **85.25** | **84.43** | **84.84** | 9116 | -| all fields (macro avg.) | 84.43 | 83.66 | 84.04 | 9116 | +| **all fields (micro avg.)** | **69.4** | **67.39** | **68.38** | 9116 | +| all fields (macro avg.) | 68.16 | 66.15 | 67.1 | 9116 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -71,14 +71,14 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 90.86 | 88.96 | 89.9 | 1911 | -| authors | 96.65 | 96.5 | 96.57 | 1941 | -| first_author | 97.47 | 97.32 | 97.4 | 1941 | -| keywords | 84.61 | 82.46 | 83.52 | 1380 | -| title | 98.24 | 97.94 | 98.09 | 1943 | +| abstract | 86.29 | 84.67 | 85.47 | 1911 | +| authors | 72.15 | 71.82 | 71.99 | 1941 | +| first_author | 88.98 | 88.56 | 88.77 | 1941 | +| keywords | 74.9 | 64.86 | 69.51 | 1380 | +| title | 92.12 | 90.89 | 91.5 | 1943 | | | | | | | -| **all fields (micro avg.)** | **94.17** | **93.28** | **93.72** | 9116 | -| all fields (macro avg.) | 93.57 | 92.64 | 93.1 | 9116 | +| **all fields (micro avg.)** | **83.52** | **81.09** | **82.28** | 9116 | +| all fields (macro avg.) | 82.89 | 80.16 | 81.45 | 9116 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -86,28 +86,28 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| abstract | 87.07 | 85.24 | 86.14 | 1911 | -| authors | 95.67 | 95.52 | 95.59 | 1941 | -| first_author | 96.8 | 96.65 | 96.73 | 1941 | -| keywords | 79.93 | 77.9 | 78.9 | 1380 | -| title | 96.18 | 95.88 | 96.03 | 1943 | +| abstract | 82.35 | 80.8 | 81.56 | 1911 | +| authors | 64.34 | 64.04 | 64.19 | 1941 | +| first_author | 88.51 | 88.1 | 88.3 | 1941 | +| keywords | 63.68 | 55.14 | 59.11 | 1380 | +| title | 86.8 | 85.64 | 86.22 | 1943 | | | | | | | -| **all fields (micro avg.)** | **91.89** | **91.02** | **91.45** | 9116 | -| all fields (macro avg.) | 91.13 | 90.24 | 90.68 | 9116 | +| **all fields (micro avg.)** | **78.21** | **75.93** | **77.05** | 9116 | +| all fields (macro avg.) | 77.14 | 74.74 | 75.88 | 9116 | #### Instance-level results ``` -Total expected instances: 1943 -Total correct instances: 216 (strict) -Total correct instances: 906 (soft) -Total correct instances: 1445 (Levenshtein) -Total correct instances: 1297 (ObservedRatcliffObershelp) - -Instance-level recall: 11.12 (strict) -Instance-level recall: 46.63 (soft) -Instance-level recall: 74.37 (Levenshtein) -Instance-level recall: 66.75 (RatcliffObershelp) +Total expected instances: 1943 +Total correct instances: 112 (strict) +Total correct instances: 483 (soft) +Total correct instances: 915 (Levenshtein) +Total correct instances: 734 (ObservedRatcliffObershelp) + +Instance-level recall: 5.76 (strict) +Instance-level recall: 24.86 (soft) +Instance-level recall: 47.09 (Levenshtein) +Instance-level recall: 37.78 (RatcliffObershelp) ``` ## Citation metadata @@ -120,17 +120,17 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 83.11 | 75.94 | 79.36 | 85778 | -| date | 94.69 | 83.83 | 88.93 | 87067 | -| first_author | 89.85 | 82.09 | 85.8 | 85778 | -| inTitle | 73.27 | 71.45 | 72.35 | 81007 | -| issue | 91.43 | 87.44 | 89.39 | 16635 | -| page | 94.68 | 83.31 | 88.63 | 80501 | -| title | 79.78 | 74.95 | 77.29 | 80736 | -| volume | 96.17 | 89.37 | 92.64 | 80067 | +| authors | 82.48 | 74.66 | 78.37 | 85778 | +| date | 94.36 | 82.52 | 88.05 | 87067 | +| first_author | 89.17 | 80.66 | 84.7 | 85778 | +| inTitle | 73.04 | 70.81 | 71.9 | 81007 | +| issue | 89.71 | 84.04 | 86.78 | 16635 | +| page | 94.22 | 83.04 | 88.28 | 80501 | +| title | 79.48 | 74.13 | 76.71 | 80736 | +| volume | 95.28 | 88.56 | 91.8 | 80067 | | | | | | | -| **all fields (micro avg.)** | **87.32** | **80.34** | **83.69** | 597569 | -| all fields (macro avg.) | 87.87 | 81.05 | 84.3 | 597569 | +| **all fields (micro avg.)** | **86.79** | **79.33** | **82.89** | 597569 | +| all fields (macro avg.) | 87.22 | 79.8 | 83.32 | 597569 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -138,17 +138,17 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 83.58 | 76.37 | 79.81 | 85778 | -| date | 94.69 | 83.83 | 88.93 | 87067 | -| first_author | 90.02 | 82.24 | 85.96 | 85778 | -| inTitle | 85.03 | 82.92 | 83.97 | 81007 | -| issue | 91.43 | 87.44 | 89.39 | 16635 | -| page | 94.68 | 83.31 | 88.63 | 80501 | -| title | 91.55 | 86.01 | 88.69 | 80736 | -| volume | 96.17 | 89.37 | 92.64 | 80067 | +| authors | 82.96 | 75.09 | 78.83 | 85778 | +| date | 94.36 | 82.52 | 88.05 | 87067 | +| first_author | 89.33 | 80.81 | 84.86 | 85778 | +| inTitle | 84.75 | 82.16 | 83.43 | 81007 | +| issue | 89.71 | 84.04 | 86.78 | 16635 | +| page | 94.22 | 83.04 | 88.28 | 80501 | +| title | 91.07 | 84.94 | 87.89 | 80736 | +| volume | 95.28 | 88.56 | 91.8 | 80067 | | | | | | | -| **all fields (micro avg.)** | **90.73** | **83.48** | **86.95** | 597569 | -| all fields (macro avg.) | 90.9 | 83.94 | 87.25 | 597569 | +| **all fields (micro avg.)** | **90.16** | **82.41** | **86.11** | 597569 | +| all fields (macro avg.) | 90.21 | 82.65 | 86.24 | 597569 | #### Levenshtein Matching (Minimum Levenshtein distance at 0.8) @@ -156,17 +156,17 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 89.29 | 81.59 | 85.27 | 85778 | -| date | 94.69 | 83.83 | 88.93 | 87067 | -| first_author | 90.24 | 82.44 | 86.17 | 85778 | -| inTitle | 86.28 | 84.14 | 85.2 | 81007 | -| issue | 91.43 | 87.44 | 89.39 | 16635 | -| page | 94.68 | 83.31 | 88.63 | 80501 | -| title | 93.9 | 88.22 | 90.97 | 80736 | -| volume | 96.17 | 89.37 | 92.64 | 80067 | +| authors | 88.75 | 80.33 | 84.33 | 85778 | +| date | 94.36 | 82.52 | 88.05 | 87067 | +| first_author | 89.55 | 81 | 85.06 | 85778 | +| inTitle | 86.03 | 83.41 | 84.7 | 81007 | +| issue | 89.71 | 84.04 | 86.78 | 16635 | +| page | 94.22 | 83.04 | 88.28 | 80501 | +| title | 93.59 | 87.29 | 90.33 | 80736 | +| volume | 95.28 | 88.56 | 91.8 | 80067 | | | | | | | -| **all fields (micro avg.)** | **92.07** | **84.72** | **88.24** | 597569 | -| all fields (macro avg.) | 92.09 | 85.04 | 88.4 | 597569 | +| **all fields (micro avg.)** | **91.55** | **83.68** | **87.44** | 597569 | +| all fields (macro avg.) | 91.44 | 83.77 | 87.42 | 597569 | #### Ratcliff/Obershelp Matching (Minimum Ratcliff/Obershelp similarity at 0.95) @@ -174,70 +174,70 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| authors | 86.05 | 78.63 | 82.18 | 85778 | -| date | 94.69 | 83.83 | 88.93 | 87067 | -| first_author | 89.87 | 82.1 | 85.81 | 85778 | -| inTitle | 83.59 | 81.52 | 82.55 | 81007 | -| issue | 91.43 | 87.44 | 89.39 | 16635 | -| page | 94.68 | 83.31 | 88.63 | 80501 | -| title | 93.5 | 87.84 | 90.58 | 80736 | -| volume | 96.17 | 89.37 | 92.64 | 80067 | +| authors | 85.4 | 77.3 | 81.15 | 85778 | +| date | 94.36 | 82.52 | 88.05 | 87067 | +| first_author | 89.18 | 80.67 | 84.71 | 85778 | +| inTitle | 83.31 | 80.77 | 82.02 | 81007 | +| issue | 89.71 | 84.04 | 86.78 | 16635 | +| page | 94.22 | 83.04 | 88.28 | 80501 | +| title | 93.09 | 86.82 | 89.85 | 80736 | +| volume | 95.28 | 88.56 | 91.8 | 80067 | | | | | | | -| **all fields (micro avg.)** | **91.12** | **83.84** | **87.33** | 597569 | -| all fields (macro avg.) | 91.25 | 84.26 | 87.59 | 597569 | +| **all fields (micro avg.)** | **90.56** | **82.77** | **86.49** | 597569 | +| all fields (macro avg.) | 90.57 | 82.97 | 86.58 | 597569 | #### Instance-level results ``` -Total expected instances: 90125 -Total extracted instances: 85141 -Total correct instances: 38534 (strict) -Total correct instances: 50633 (soft) -Total correct instances: 55471 (Levenshtein) -Total correct instances: 52032 (RatcliffObershelp) +Total expected instances: 90125 +Total extracted instances: 86125 +Total correct instances: 37732 (strict) +Total correct instances: 49502 (soft) +Total correct instances: 54240 (Levenshtein) +Total correct instances: 50880 (RatcliffObershelp) -Instance-level precision: 45.26 (strict) -Instance-level precision: 59.47 (soft) -Instance-level precision: 65.15 (Levenshtein) -Instance-level precision: 61.11 (RatcliffObershelp) +Instance-level precision: 43.81 (strict) +Instance-level precision: 57.48 (soft) +Instance-level precision: 62.98 (Levenshtein) +Instance-level precision: 59.08 (RatcliffObershelp) -Instance-level recall: 42.76 (strict) -Instance-level recall: 56.18 (soft) -Instance-level recall: 61.55 (Levenshtein) -Instance-level recall: 57.73 (RatcliffObershelp) +Instance-level recall: 41.87 (strict) +Instance-level recall: 54.93 (soft) +Instance-level recall: 60.18 (Levenshtein) +Instance-level recall: 56.45 (RatcliffObershelp) -Instance-level f-score: 43.97 (strict) -Instance-level f-score: 57.78 (soft) -Instance-level f-score: 63.3 (Levenshtein) -Instance-level f-score: 59.37 (RatcliffObershelp) +Instance-level f-score: 42.82 (strict) +Instance-level f-score: 56.17 (soft) +Instance-level f-score: 61.55 (Levenshtein) +Instance-level f-score: 57.74 (RatcliffObershelp) -Matching 1 : 67991 +Matching 1 : 66746 -Matching 2 : 4123 +Matching 2 : 4079 -Matching 3 : 1868 +Matching 3 : 2288 -Matching 4 : 661 +Matching 4 : 986 -Total matches : 74643 +Total matches : 74099 ``` #### Citation context resolution ``` -Total expected references: 90125 - 46.38 references per article -Total predicted references: 85141 - 43.82 references per article +Total expected references: 90125 - 46.38 references per article +Total predicted references: 86125 - 44.33 references per article -Total expected citation contexts: 139835 - 71.97 citation contexts per article -Total predicted citation contexts: 114496 - 58.93 citation contexts per article +Total expected citation contexts: 139835 - 71.97 citation contexts per article +Total predicted citation contexts: 112840 - 58.08 citation contexts per article -Total correct predicted citation contexts: 96976 - 49.91 citation contexts per article -Total wrong predicted citation contexts: 17520 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) +Total correct predicted citation contexts: 95258 - 49.03 citation contexts per article +Total wrong predicted citation contexts: 17582 (wrong callout matching, callout missing in NLM, or matching with a bib. ref. not aligned with a bib.ref. in NLM) -Precision citation contexts: 84.7 -Recall citation contexts: 69.35 -fscore citation contexts: 76.26 +Precision citation contexts: 84.42 +Recall citation contexts: 68.12 +fscore citation contexts: 75.4 ``` ## Fulltext structures @@ -253,17 +253,17 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). **Field-level results** -| label | precision | recall | f1 | support | -|-----------------------------|-----------|----------|-----------|---------| -| figure_title | 31.53 | 26.55 | 28.82 | 7281 | -| reference_citation | 58.14 | 58.76 | 58.45 | 134196 | -| reference_figure | 60.59 | 68.27 | 64.2 | 19330 | -| reference_table | 82.87 | 89.52 | 86.06 | 7327 | -| section_title | 73.58 | 67.75 | 70.55 | 27619 | -| table_title | 67.76 | 49.58 | 57.26 | 3971 | -| | | | | | -| **all fields (micro avg.)** | **60.68** | **60.7** | **60.69** | 199724 | -| all fields (macro avg.) | 62.41 | 60.07 | 60.89 | 199724 | +| label | precision | recall | f1 | support | +|-----------------------------|-----------|-----------|-----------|---------| +| figure_title | 31.63 | 26.59 | 28.89 | 7281 | +| reference_citation | 58.1 | 58.67 | 58.38 | 134196 | +| reference_figure | 60.63 | 68.29 | 64.23 | 19330 | +| reference_table | 82.88 | 89.57 | 86.09 | 7327 | +| section_title | 73.73 | 67.79 | 70.64 | 27619 | +| table_title | 67.71 | 49.58 | 57.25 | 3971 | +| | | | | | +| **all fields (micro avg.)** | **60.67** | **60.65** | **60.66** | 199724 | +| all fields (macro avg.) | 62.45 | 60.08 | 60.91 | 199724 | #### Soft Matching (ignoring punctuation, case and space characters mismatches) @@ -271,15 +271,15 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | label | precision | recall | f1 | support | |-----------------------------|-----------|-----------|-----------|---------| -| figure_title | 79.55 | 66.98 | 72.73 | 7281 | -| reference_citation | 62.42 | 63.09 | 62.75 | 134196 | -| reference_figure | 61.09 | 68.84 | 64.73 | 19330 | -| reference_table | 83.04 | 89.71 | 86.25 | 7327 | -| section_title | 79.09 | 72.82 | 75.83 | 27619 | -| table_title | 94.22 | 68.95 | 79.63 | 3971 | +| figure_title | 79.43 | 66.78 | 72.56 | 7281 | +| reference_citation | 62.35 | 62.96 | 62.65 | 134196 | +| reference_figure | 61.12 | 68.85 | 64.76 | 19330 | +| reference_table | 83.05 | 89.76 | 86.28 | 7327 | +| section_title | 79.24 | 72.85 | 75.91 | 27619 | +| table_title | 94.19 | 68.98 | 79.63 | 3971 | | | | | | | -| **all fields (micro avg.)** | **66.2** | **66.22** | **66.21** | 199724 | -| all fields (macro avg.) | 76.57 | 71.73 | 73.65 | 199724 | +| **all fields (micro avg.)** | **66.17** | **66.14** | **66.16** | 199724 | +| all fields (macro avg.) | 76.56 | 71.7 | 73.63 | 199724 | **Document-level ratio results** @@ -289,4 +289,4 @@ Evaluation on 1943 random PDF files out of 1941 PDF (ratio 1.0). | **all fields (micro avg.)** | **0** | **0** | **0** | 0 | | all fields (macro avg.) | 0 | 0 | 0 | 0 | -Evaluation metrics produced in 1311.519 seconds +Evaluation metrics produced in 1263.288 seconds diff --git a/grobid-core/src/main/java/org/grobid/core/engines/CitationParser.java b/grobid-core/src/main/java/org/grobid/core/engines/CitationParser.java index 24f5cbcf12..8b606efa68 100755 --- a/grobid-core/src/main/java/org/grobid/core/engines/CitationParser.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/CitationParser.java @@ -59,33 +59,34 @@ public CitationParser(EngineParsers parsers) { /** * Process one single raw reference string - */ + */ public BiblioItem processingString(String input, int consolidate) { List inputs = new ArrayList<>(); - input = TextUtilities.removeLeadingAndTrailingChars(input, "[({.,])}: \n"," \n"); + input = TextUtilities.removeLeadingAndTrailingChars(input, "[({.,])}: \n", " \n"); inputs.add(input); List result = processingStringMultiple(inputs, consolidate); - if (result != null && result.size()>0) + if (result != null && result.size() > 0) return result.get(0); else return null; } /** - * Process a list of raw reference strings by taking advantage of batch processing + * Process a list of raw reference strings by taking advantage of batch + * processing * when a DeLFT deep learning model is used - */ + */ public List processingStringMultiple(List inputs, int consolidate) { if (inputs == null || inputs.size() == 0) return null; List> tokenList = new ArrayList<>(); - for(String input : inputs) { - if (StringUtils.isBlank(input)) + for (String input : inputs) { + if (StringUtils.isBlank(input)) tokenList.add(new ArrayList()); else { // some cleaning input = UnicodeUtil.normaliseText(input); - input = TextUtilities.removeLeadingAndTrailingChars(input, "[({.,])}: \n"," \n"); + input = TextUtilities.removeLeadingAndTrailingChars(input, "[({.,])}: \n", " \n"); List tokens = analyzer.tokenizeWithLayoutToken(input); tokens = analyzer.retokenizeSubdigitsFromLayoutToken(tokens); tokenList.add(tokens); @@ -99,7 +100,7 @@ public List processingStringMultiple(List inputs, int consol for (BiblioItem result : results) { if (result != null) { String localInput = inputs.get(i); - localInput = TextUtilities.removeLeadingAndTrailingChars(localInput, "[({.,])}: \n"," \n"); + localInput = TextUtilities.removeLeadingAndTrailingChars(localInput, "[({.,])}: \n", " \n"); result.setReference(localInput); } i++; @@ -110,21 +111,22 @@ public List processingStringMultiple(List inputs, int consol /** * Process one single raw reference string tokenized as layout objects - */ + */ public BiblioItem processingLayoutToken(List tokens, int consolidate) { List> tokenList = new ArrayList<>(); tokenList.add(tokens); List result = processingLayoutTokenMultiple(tokenList, consolidate); - if (result != null && result.size()>0) + if (result != null && result.size() > 0) return result.get(0); else return null; } /** - * Process a list of raw reference string, each one tokenized as layout objects, and taking advantage + * Process a list of raw reference string, each one tokenized as layout objects, + * and taking advantage * of batch processing when a DeLFT deep learning model is used - */ + */ public List processingLayoutTokenMultiple(List> tokenList, int consolidate) { if (tokenList == null || tokenList.size() == 0) return null; @@ -132,7 +134,7 @@ public List processingLayoutTokenMultiple(List> to StringBuilder featuredInput = new StringBuilder(); int p = 0; - for(List tokens : tokenList) { + for (List tokens : tokenList) { tokenList.set(p, analyzer.retokenizeSubdigitsFromLayoutToken(tokens)); p++; } @@ -151,9 +153,9 @@ public List processingLayoutTokenMultiple(List> to List urlPositions = lexicon.tokenPositionsUrlPattern(tokens); try { - String featuredBlock = FeaturesVectorCitation.addFeaturesCitation(tokens, null, journalsPositions, - abbrevJournalsPositions, conferencesPositions, publishersPositions, locationsPositions, - collaborationsPositions, identifiersPositions, urlPositions); + String featuredBlock = FeaturesVectorCitation.addFeaturesCitation(tokens, null, journalsPositions, + abbrevJournalsPositions, conferencesPositions, publishersPositions, locationsPositions, + collaborationsPositions, identifiersPositions, urlPositions); featuredInput.append(featuredBlock); featuredInput.append("\n\n"); @@ -161,8 +163,8 @@ public List processingLayoutTokenMultiple(List> to LOGGER.error("An exception occured while adding features for processing a citation.", e); } } - - if (featuredInput.toString().length() == 0) + + if (featuredInput.toString().length() == 0) return null; String allRes = null; @@ -176,23 +178,39 @@ public List processingLayoutTokenMultiple(List> to if (allRes == null || allRes.length() == 0) return null; - String[] resBlocks = allRes.split("\n\n"); + // Use regex to split on one or more consecutive empty lines, and filter empty + // blocks + String[] resBlocksRaw = allRes.split("\n\n+"); + List resBlocksList = new ArrayList<>(); + for (String block : resBlocksRaw) { + String trimmed = block.trim(); + if (!trimmed.isEmpty()) { + resBlocksList.add(trimmed); + } + } + String[] resBlocks = resBlocksList.toArray(new String[0]); int i = 0; for (List tokens : tokenList) { if (CollectionUtils.isEmpty(tokens)) results.add(null); else { + if (i >= resBlocks.length) { + LOGGER.warn("Mismatch between tokenList size and result blocks: expected more blocks"); + results.add(null); + continue; + } String res = resBlocks[i]; i++; BiblioItem resCitation = resultExtractionLayoutTokens(res, true, tokens); - + // post-processing (additional field parsing and cleaning) if (resCitation != null) { BiblioItem.cleanTitles(resCitation); resCitation.setOriginalAuthors(resCitation.getAuthors()); try { - resCitation.setFullAuthors(parsers.getAuthorParser().processingCitation(resCitation.getAuthors())); + resCitation + .setFullAuthors(parsers.getAuthorParser().processingCitation(resCitation.getAuthors())); } catch (Exception e) { LOGGER.error("An exception occured when processing author names of a citation.", e); } @@ -230,7 +248,8 @@ public List processingLayoutTokenMultiple(List> to // editors (they are human persons in theory) resCitation.setOriginalEditors(resCitation.getEditors()); try { - resCitation.setFullEditors(parsers.getAuthorParser().processingCitation(resCitation.getEditors())); + resCitation + .setFullEditors(parsers.getAuthorParser().processingCitation(resCitation.getEditors())); } catch (Exception e) { LOGGER.error("An exception occured when processing editor names of a citation.", e); } @@ -244,7 +263,8 @@ public List processingLayoutTokenMultiple(List> to return results; } - public List processingReferenceSection(String referenceTextBlock, ReferenceSegmenter referenceSegmenter) { + public List processingReferenceSection(String referenceTextBlock, + ReferenceSegmenter referenceSegmenter) { List segm = referenceSegmenter.extract(referenceTextBlock); List results = new ArrayList<>(); @@ -255,7 +275,7 @@ public List processingReferenceSection(String referenceTextBlock, Re if (ref.getTokens() == null || ref.getTokens().size() == 0) continue; List localTokens = ref.getTokens(); - localTokens = TextUtilities.removeLeadingAndTrailingCharsLayoutTokens(localTokens, "[({.,])}: \n"," \n"); + localTokens = TextUtilities.removeLeadingAndTrailingCharsLayoutTokens(localTokens, "[({.,])}: \n", " \n"); allRefBlocks.add(localTokens); } @@ -269,13 +289,13 @@ public List processingReferenceSection(String referenceTextBlock, Re if ((bib != null) && !bib.rejectAsReference()) { BibDataSet bds = new BibDataSet(); String localLabel = ref.getLabel(); - if (localLabel != null && localLabel.length()>0) { + if (localLabel != null && localLabel.length() > 0) { // cleaning the label for matching localLabel = TextUtilities.removeLeadingAndTrailingChars(localLabel, "([{<,. \n", ")}]>,.: \n"); } String localRef = ref.getReferenceText(); - localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, "[({.,])}: \n"," \n"); + localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, "[({.,])}: \n", " \n"); bds.setRefSymbol(localLabel); bib.setReference(localRef); bds.setResBib(bib); @@ -287,7 +307,8 @@ public List processingReferenceSection(String referenceTextBlock, Re return results; } - public List processingReferenceSection(Document doc, ReferenceSegmenter referenceSegmenter, int consolidate) { + public List processingReferenceSection(Document doc, ReferenceSegmenter referenceSegmenter, + int consolidate) { List results = new ArrayList<>(); String referencesStr = doc.getDocumentPartText(SegmentationLabels.REFERENCES); @@ -308,71 +329,75 @@ public List processingReferenceSection(Document doc, ReferenceSegmen cntManager.i(CitationParserCounters.SEGMENTED_REFERENCES, references.size()); } - // consolidation: if selected, it is NOT done individually for each citation but + // consolidation: if selected, it is NOT done individually for each citation but // in a second stage for all citations if (references != null) { - /*List refTexts = new ArrayList<>(); - for (LabeledReferenceResult ref : references) { - // paranoiac check - if (ref == null) - continue; - - String localRef = ref.getReferenceText(); - localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, "[({.,])}: \n"," \n"); - refTexts.add(localRef); - } - List bibList = processingStringMultiple(refTexts, 0);*/ + /* + * List refTexts = new ArrayList<>(); + * for (LabeledReferenceResult ref : references) { + * // paranoiac check + * if (ref == null) + * continue; + * + * String localRef = ref.getReferenceText(); + * localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, + * "[({.,])}: \n"," \n"); + * refTexts.add(localRef); + * } + * List bibList = processingStringMultiple(refTexts, 0); + */ List> allRefBlocks = new ArrayList<>(); for (LabeledReferenceResult ref : references) { // paranoiac check - if (ref == null) + if (ref == null) continue; List localTokens = ref.getTokens(); - localTokens = TextUtilities.removeLeadingAndTrailingCharsLayoutTokens(localTokens, "[({.,])}: \n"," \n"); + localTokens = TextUtilities.removeLeadingAndTrailingCharsLayoutTokens(localTokens, "[({.,])}: \n", + " \n"); allRefBlocks.add(localTokens); } List bibList = processingLayoutTokenMultiple(allRefBlocks, 0); - if (bibList != null && bibList.size()>0) { + if (bibList != null && bibList.size() > 0) { int i = 0; for (LabeledReferenceResult ref : references) { // paranoiac check - if (ref == null) + if (ref == null) continue; - //BiblioItem bib = processingString(ref.getReferenceText(), 0); + // BiblioItem bib = processingString(ref.getReferenceText(), 0); BiblioItem bib = bibList.get(i); i++; - if (bib == null) + if (bib == null) continue; // check if we have an interesting url annotation over this bib. ref. List refTokens = ref.getTokens(); if ((refTokens != null) && (refTokens.size() > 0)) { List localPages = new ArrayList(); - for(LayoutToken token : refTokens) { + for (LayoutToken token : refTokens) { if (!localPages.contains(token.getPage())) { localPages.add(token.getPage()); } } - for(PDFAnnotation annotation : doc.getPDFAnnotations()) { - if (annotation.getType() != Type.URI) + for (PDFAnnotation annotation : doc.getPDFAnnotations()) { + if (annotation.getType() != Type.URI) continue; if (!localPages.contains(annotation.getPageNumber())) continue; - for(LayoutToken token : refTokens) { + for (LayoutToken token : refTokens) { if (annotation.cover(token)) { // annotation covers tokens, let's look at the href String uri = annotation.getDestination(); // is it a DOI? Matcher doiMatcher = TextUtilities.DOIPattern.matcher(uri); - if (doiMatcher.find()) { - // the BiblioItem setter will take care of the prefix and doi cleaninng + if (doiMatcher.find()) { + // the BiblioItem setter will take care of the prefix and doi cleaninng bib.setDOI(uri); } - // TBD: is it something else? + // TBD: is it something else? } } } @@ -381,13 +406,14 @@ public List processingReferenceSection(Document doc, ReferenceSegmen if (!bib.rejectAsReference()) { BibDataSet bds = new BibDataSet(); String localLabel = ref.getLabel(); - if (localLabel != null && localLabel.length()>0) { + if (localLabel != null && localLabel.length() > 0) { // cleaning the label for matching - localLabel = TextUtilities.removeLeadingAndTrailingChars(localLabel, "([{<,. \n", ")}]>,.: \n"); + localLabel = TextUtilities.removeLeadingAndTrailingChars(localLabel, "([{<,. \n", + ")}]>,.: \n"); } String localRef = ref.getReferenceText(); - localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, "[({.,])}: \n"," \n"); + localRef = TextUtilities.removeLeadingAndTrailingChars(localRef, "[({.,])}: \n", " \n"); bds.setRefSymbol(localLabel); bds.setResBib(bib); @@ -404,16 +430,16 @@ public List processingReferenceSection(Document doc, ReferenceSegmen if (consolidate != 0) { Consolidation consolidator = Consolidation.getInstance(); if (consolidator.getCntManager() == null) - consolidator.setCntManager(cntManager); - Map resConsolidation = null; + consolidator.setCntManager(cntManager); + Map resConsolidation = null; try { resConsolidation = consolidator.consolidate(results); - } catch(Exception e) { + } catch (Exception e) { throw new GrobidException( - "An exception occured while running consolidation on bibliographical references.", e); - } + "An exception occured while running consolidation on bibliographical references.", e); + } if (resConsolidation != null) { - for(int i=0; i processingReferenceSection(File input, - ReferenceSegmenter referenceSegmenter, - int consolidate) { + ReferenceSegmenter referenceSegmenter, + int consolidate) { DocumentSource documentSource = DocumentSource.fromPdf(input); return processingReferenceSection(documentSource, referenceSegmenter, consolidate); } public List processingReferenceSection(File input, - String md5Str, - ReferenceSegmenter referenceSegmenter, - int consolidate) { + String md5Str, + ReferenceSegmenter referenceSegmenter, + int consolidate) { DocumentSource documentSource = DocumentSource.fromPdf(input); documentSource.setMD5(md5Str); return processingReferenceSection(documentSource, referenceSegmenter, consolidate); } public List processingReferenceSection(DocumentSource documentSource, - ReferenceSegmenter referenceSegmenter, - int consolidate) { + ReferenceSegmenter referenceSegmenter, + int consolidate) { List results; try { Document doc = parsers.getSegmentationParser().processing(documentSource, @@ -466,7 +492,6 @@ public List processingReferenceSection(DocumentSource documentSource return results; } - /** * Extract results from a labeled sequence. * @@ -476,8 +501,8 @@ public List processingReferenceSection(DocumentSource documentSource * @return biblio item */ public BiblioItem resultExtractionLayoutTokens(String result, - boolean volumePostProcess, - List tokenizations) { + boolean volumePostProcess, + List tokenizations) { BiblioItem biblio = new BiblioItem(); TaggingLabel lastClusterLabel = null; @@ -494,10 +519,12 @@ public BiblioItem resultExtractionLayoutTokens(String result, TaggingLabel clusterLabel = cluster.getTaggingLabel(); Engine.getCntManager().i(clusterLabel); - //String clusterContent = LayoutTokensUtil.normalizeText(LayoutTokensUtil.toText(cluster.concatTokens())); - //String clusterContent = LayoutTokensUtil.toText(cluster.concatTokens()); + // String clusterContent = + // LayoutTokensUtil.normalizeText(LayoutTokensUtil.toText(cluster.concatTokens())); + // String clusterContent = LayoutTokensUtil.toText(cluster.concatTokens()); String clusterContent = LayoutTokensUtil.normalizeDehyphenizeText(cluster.concatTokens()); - //String clusterNonDehypenizedContent = LayoutTokensUtil.toText(cluster.concatTokens()); + // String clusterNonDehypenizedContent = + // LayoutTokensUtil.toText(cluster.concatTokens()); if (clusterLabel.equals(TaggingLabels.CITATION_TITLE)) { if (biblio.getTitle() == null) biblio.setTitle(clusterContent); @@ -555,7 +582,7 @@ else if (biblio.getSerieTitle().length() >= clusterContent.length()) { } else if (clusterLabel.equals(TaggingLabels.CITATION_JOURNAL)) { if (biblio.getJournal() == null) { biblio.setJournal(clusterContent); - }else if (biblio.getJournal().length() >= clusterContent.length()) { + } else if (biblio.getJournal().length() >= clusterContent.length()) { biblio.setNoteOrConcatenateIfNotEmpty(clusterContent); } else { biblio.setNoteOrConcatenateIfNotEmpty(biblio.getJournal()); @@ -577,7 +604,7 @@ else if (biblio.getSerieTitle().length() >= clusterContent.length()) { } else { biblio.setInstitution(clusterContent); } - } else if (clusterLabel.equals(TaggingLabels.CITATION_NOTE)) { + } else if (clusterLabel.equals(TaggingLabels.CITATION_NOTE)) { biblio.setNoteOrConcatenateIfNotEmpty(clusterContent); } else if (clusterLabel.equals(TaggingLabels.CITATION_PUBNUM)) { String clusterNonDehypenizedContent = LayoutTokensUtil.toText(cluster.concatTokens()); @@ -587,7 +614,7 @@ else if (biblio.getSerieTitle().length() >= clusterContent.length()) { String clusterNonDehypenizedContent = LayoutTokensUtil.toText(cluster.concatTokens()); biblio.setWeb(clusterNonDehypenizedContent); } - } + } return biblio; } @@ -601,21 +628,21 @@ else if (biblio.getSerieTitle().length() >= clusterContent.length()) { */ public BiblioItem consolidateCitation(BiblioItem resCitation, String rawCitation, int consolidate) { if (consolidate == 0) { - // no consolidation + // no consolidation return resCitation; } Consolidation consolidator = null; try { consolidator = Consolidation.getInstance(); if (consolidator.getCntManager() == null) - consolidator.setCntManager(cntManager); + consolidator.setCntManager(cntManager); List biblios = new ArrayList(); BibDataSet theBib = new BibDataSet(); theBib.setResBib(resCitation); biblios.add(theBib); - Map bibis = consolidator.consolidate(biblios); + Map bibis = consolidator.consolidate(biblios); - //BiblioItem bibo = consolidator.consolidate(resCitation, rawCitation); + // BiblioItem bibo = consolidator.consolidate(resCitation, rawCitation); BiblioItem bibo = bibis.get(0); if (bibo != null) { if (consolidate == 1) @@ -627,7 +654,7 @@ else if (consolidate == 2) LOGGER.error("An exception occurred while running bibliographical data consolidation.", e); throw new GrobidException( "An exception occurred while running bibliographical data consolidation.", e); - } + } return resCitation; } @@ -675,12 +702,11 @@ public StringBuilder trainingExtraction(List inputs) { urlPositions = lexicon.tokenPositionsUrlPattern(tokenizations); String ress = FeaturesVectorCitation.addFeaturesCitation(tokenizations, - null, journalsPositions, abbrevJournalsPositions, - conferencesPositions, publishersPositions, locationsPositions, + null, journalsPositions, abbrevJournalsPositions, + conferencesPositions, publishersPositions, locationsPositions, collaborationsPositions, identifiersPositions, urlPositions); String res = label(ress); - String lastTag = null; String lastTag0; String currentTag0 = null; @@ -697,7 +723,7 @@ public StringBuilder trainingExtraction(List inputs) { if (tok.length() == 0) { // new citation - //buffer.append("/t\n"); + // buffer.append("/t\n"); start = true; continue; } @@ -710,7 +736,7 @@ public StringBuilder trainingExtraction(List inputs) { String s = stt.nextToken().trim(); if (i == 0) { s2 = TextUtilities.HTMLEncode(s); - //s2 = s; + // s2 = s; boolean strop = false; while ((!strop) && (p < tokenizations.size())) { @@ -725,7 +751,7 @@ public StringBuilder trainingExtraction(List inputs) { } } else if (i == ll - 1) { s1 = s; - } + } i++; } @@ -750,7 +776,7 @@ public StringBuilder trainingExtraction(List inputs) { } } - //tagClosed = lastTag0 != null && + // tagClosed = lastTag0 != null && if ((lastTag0 != null) && (currentTag0 != null)) testClosingTag(buffer, currentTag0, lastTag0); @@ -760,52 +786,53 @@ public StringBuilder trainingExtraction(List inputs) { } if (output == null) { output = writeField(s1, lastTag0, s2, "", "", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "", "", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<series>", "<title level=\"s\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<booktitle>", "<title level=\"m\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<date>", "<date>", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<volume>", "<biblScope unit=\"volume\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<publisher>", "<publisher>", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<location>", "<pubPlace>", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<editor>", "<editor>", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<pages>", "<biblScope unit=\"page\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<tech>", "<note type=\"report\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<issue>", "<biblScope unit=\"issue\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<web>", "<ptr type=\"web\">", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<note>", "<note>", addSpace, 0); - } + } if (output == null) { output = writeField(s1, lastTag0, s2, "<institution>", "<orgName>", addSpace, 0); - } + } if (output == null) { - output = writeField(s1, lastTag0, s2, "<collaboration>", "<orgName type=\"collaboration\">", addSpace, 0); - } + output = writeField(s1, lastTag0, s2, "<collaboration>", "<orgName type=\"collaboration\">", + addSpace, 0); + } if (output == null) { String localTag = null; String cleanS2 = StringUtils.normalizeSpace(s2); @@ -820,16 +847,16 @@ public StringBuilder trainingExtraction(List<String> inputs) { if (arxivMatcher.find()) localTag = "<idno type=\"arXiv\">"; } - + if (localTag == null) { Matcher pmidMatcher = TextUtilities.pmidPattern.matcher(cleanS2); - if (pmidMatcher.find()) + if (pmidMatcher.find()) localTag = "<idno type=\"PMID\">"; } if (localTag == null) { Matcher pmcidMatcher = TextUtilities.pmcidPattern.matcher(cleanS2); - if (pmcidMatcher.find()) + if (pmcidMatcher.find()) localTag = "<idno type=\"PMC\">"; } @@ -851,7 +878,7 @@ public StringBuilder trainingExtraction(List<String> inputs) { localTag = "<idno>"; output = writeField(s1, lastTag0, s2, "<pubnum>", localTag, addSpace, 0); - } + } if (output != null) { buffer.append(output); lastTag = s1; @@ -871,7 +898,7 @@ public StringBuilder trainingExtraction(List<String> inputs) { buffer.append("</bibl>\n"); } } - + } catch (Exception e) { throw new GrobidException("An exception occured while running Grobid.", e); } @@ -879,7 +906,7 @@ public StringBuilder trainingExtraction(List<String> inputs) { } private String writeField(String s1, String lastTag0, String s2, - String field, String outField, boolean addSpace, int nbIndent) { + String field, String outField, boolean addSpace, int nbIndent) { String result = null; if ((s1.equals(field)) || (s1.equals("I-" + field))) { if (s1.equals(lastTag0) || s1.equals("I-" + lastTag0)) { @@ -889,9 +916,11 @@ private String writeField(String s1, String lastTag0, String s2, result = s2; } else { result = ""; - /*for (int i = 0; i < nbIndent; i++) { - result += "\t"; - }*/ + /* + * for (int i = 0; i < nbIndent; i++) { + * result += "\t"; + * } + */ if (addSpace) { result += " " + outField + s2; } else { @@ -902,7 +931,8 @@ private String writeField(String s1, String lastTag0, String s2, return result; } - private boolean writeField2(StringBuilder buffer, String s1, String lastTag0, String s2, String field, String outField, boolean addSpace) { + private boolean writeField2(StringBuilder buffer, String s1, String lastTag0, String s2, String field, + String outField, boolean addSpace) { boolean result = false; if ((s1.equals(field)) || (s1.equals("I-" + field))) { result = true; @@ -922,7 +952,7 @@ private boolean writeField2(StringBuilder buffer, String s1, String lastTag0, St } private boolean testClosingTag(StringBuilder buffer, String currentTag0, - String lastTag0) { + String lastTag0) { boolean res = false; if (!currentTag0.equals(lastTag0)) { res = true; diff --git a/grobid-core/src/main/java/org/grobid/core/engines/HeaderParser.java b/grobid-core/src/main/java/org/grobid/core/engines/HeaderParser.java index 14b76a04a3..9f14077598 100755 --- a/grobid-core/src/main/java/org/grobid/core/engines/HeaderParser.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/HeaderParser.java @@ -340,7 +340,10 @@ public String processingHeaderSection( // copyrights/license identification if (StringUtils.isNotBlank(resHeader.getCopyright())) { - if (GrobidProperties.getGrobidEngineName("copyright").equals("delft")) { + if ( + GrobidProperties.getGrobidEngineName("copyright").equals("delft") + || GrobidProperties.getGrobidEngineName("copyright").equals("onnx") + ){ CopyrightsLicense copyrightsLicense = LicenseClassifier.getInstance().classify(resHeader.getCopyright()); if (copyrightsLicense != null) resHeader.setCopyrightsLicense(copyrightsLicense); @@ -579,35 +582,10 @@ else if (previousLineStartX - lineStartX > characterWidth) continue; } - features = new FeaturesVectorHeader(); - features.token = token; - features.string = text; + features = FeaturesVectorHeader.fromLayoutToken(token); if (newline) features.lineStatus = "LINESTART"; - - Matcher m0 = featureFactory.isPunct.matcher(text); - if (m0.find()) { - features.punctType = "PUNCT"; - } - if (text.equals("(") || text.equals("[")) { - features.punctType = "OPENBRACKET"; - - } else if (text.equals(")") || text.equals("]")) { - features.punctType = "ENDBRACKET"; - - } else if (text.equals(".")) { - features.punctType = "DOT"; - - } else if (text.equals(",")) { - features.punctType = "COMMA"; - - } else if (text.equals("-")) { - features.punctType = "HYPHEN"; - - } else if (text.equals("\"") || text.equals("\'") || text.equals("`")) { - features.punctType = "QUOTE"; - } if (n == startIndex) { // beginning of block @@ -677,43 +655,6 @@ else if (features.blockStatus == null) features.alignmentStatus = "ALIGNEDLEFT"; } - if (text.length() == 1) { - features.singleChar = true; - } - - if (Character.isUpperCase(text.charAt(0))) { - features.capitalisation = "INITCAP"; - } - - if (featureFactory.test_all_capital(text)) { - features.capitalisation = "ALLCAP"; - } - - if (featureFactory.test_digit(text)) { - features.digit = "CONTAINSDIGITS"; - } - - Matcher m = featureFactory.isDigit.matcher(text); - if (m.find()) { - features.digit = "ALLDIGIT"; - } - - if (featureFactory.test_common(text)) { - features.commonName = true; - } - - if (featureFactory.test_names(text)) { - features.properName = true; - } - - if (featureFactory.test_month(text)) { - features.month = true; - } - - Matcher m2 = featureFactory.year.matcher(text); - if (m2.find()) { - features.year = true; - } // check token offsets for email and http address, or known location if (locationPositions != null) { @@ -775,21 +716,6 @@ else if (features.blockStatus == null) /*if (token.isSuperscript()) features.superscript = true;*/ - if (token.isBold()) - features.bold = true; - - if (token.isItalic()) - features.italic = true; - - if (features.capitalisation == null) - features.capitalisation = "NOCAPS"; - - if (features.digit == null) - features.digit = "NODIGIT"; - - if (features.punctType == null) - features.punctType = "NOPUNCT"; - /*if (spacingPreviousBlock != 0.0) { features.spacingWithPreviousBlock = featureFactory .linearScaling(spacingPreviousBlock-doc.getMinBlockSpacing(), doc.getMaxBlockSpacing()-doc.getMinBlockSpacing(), NBBINS_SPACE); diff --git a/grobid-core/src/main/java/org/grobid/core/engines/LicenseClassifier.java b/grobid-core/src/main/java/org/grobid/core/engines/LicenseClassifier.java index 0672d994e8..0f46baf38a 100644 --- a/grobid-core/src/main/java/org/grobid/core/engines/LicenseClassifier.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/LicenseClassifier.java @@ -8,8 +8,8 @@ import org.grobid.core.data.CopyrightsLicense; import org.grobid.core.data.CopyrightsLicense.CopyrightsOwner; import org.grobid.core.data.CopyrightsLicense.License; -import org.grobid.core.utilities.GrobidProperties; -import org.grobid.core.jni.DeLFTClassifierModel; +import org.grobid.core.engines.tagging.ClassifierFactory; +import org.grobid.core.engines.tagging.GenericClassifier; import com.fasterxml.jackson.core.*; import com.fasterxml.jackson.databind.*; @@ -22,11 +22,11 @@ public class LicenseClassifier { private static final Logger LOGGER = LoggerFactory.getLogger(LicenseClassifier.class); // multi-class/multi-label classifier - private DeLFTClassifierModel classifierCopyrightsOwner = null; - private DeLFTClassifierModel classifierLicense = null; + private GenericClassifier classifierCopyrightsOwner = null; + private GenericClassifier classifierLicense = null; // binary classifiers to be added if used - private Boolean useBinary = false; + private Boolean useBinary = false; private JsonParser parser; @@ -51,12 +51,13 @@ private static synchronized void getNewInstance() { } private LicenseClassifier() { - this.classifierCopyrightsOwner = new DeLFTClassifierModel("copyright", GrobidProperties.getDelftArchitecture("copyright")); - this.classifierLicense = new DeLFTClassifierModel("license", GrobidProperties.getDelftArchitecture("license")); + this.classifierCopyrightsOwner = ClassifierFactory.getClassifier("copyright"); + this.classifierLicense = ClassifierFactory.getClassifier("license"); } /** * Classify a simple piece of text + * * @return list of predicted labels/scores pairs */ public CopyrightsLicense classify(String text) throws Exception { @@ -69,13 +70,14 @@ public CopyrightsLicense classify(String text) throws Exception { /** * Classify an array of texts + * * @return list of predicted labels/scores pairs for each text */ public List<CopyrightsLicense> classify(List<String> texts) throws Exception { if (CollectionUtils.isEmpty(texts)) return null; - LOGGER.info("classify: " + texts.size()); + LOGGER.debug("classify: " + texts.size()); String copyrightOwnerAsJson = this.classifierCopyrightsOwner.classify(texts); String licencesAsJson = this.classifierLicense.classify(texts); @@ -92,11 +94,11 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ JsonNode root_copyrights = mapper.readTree(copyrightOwnerAsJson); JsonNode root_licenses = mapper.readTree(licencesAsJson); - int entityRank =0; + int entityRank = 0; JsonNode classificationsNodeCopyrights = root_copyrights.findPath("classifications"); JsonNode classificationsNodeLicenses = root_licenses.findPath("classifications"); - if ((classificationsNodeCopyrights != null) && (!classificationsNodeCopyrights.isMissingNode()) && - (classificationsNodeLicenses != null) && (!classificationsNodeLicenses.isMissingNode())) { + if ((classificationsNodeCopyrights != null) && (!classificationsNodeCopyrights.isMissingNode()) && + (classificationsNodeLicenses != null) && (!classificationsNodeLicenses.isMissingNode())) { Iterator<JsonNode> ite1 = classificationsNodeCopyrights.elements(); Iterator<JsonNode> ite2 = classificationsNodeLicenses.elements(); while (ite1.hasNext()) { @@ -106,7 +108,7 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ List<String> owners = CopyrightsLicense.copyrightOwners; List<Double> scoreFields = new ArrayList<>(); - for(String fieldOwners : owners) { + for (String fieldOwners : owners) { JsonNode fieldNode = classificationsNode.findPath(fieldOwners); double scoreField = 0.0; if ((fieldNode != null) && (!fieldNode.isMissingNode())) { @@ -119,7 +121,7 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ double scoreUndecided = 0.0; int rank = 0; for (Double scoreField : scoreFields) { - if (scoreField>0.5 && scoreField > bestProb) { + if (scoreField > 0.5 && scoreField > bestProb) { owner = CopyrightsOwner.valueOf(owners.get(rank).toUpperCase()); bestProb = scoreField; } @@ -142,7 +144,7 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ List<String> licenses = CopyrightsLicense.licenses; scoreFields = new ArrayList<>(); - for(String fieldLicenses : licenses) { + for (String fieldLicenses : licenses) { JsonNode fieldNode = classificationsNode.findPath(fieldLicenses); double scoreField = 0.0; if ((fieldNode != null) && (!fieldNode.isMissingNode())) { @@ -155,7 +157,7 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ License license = null; rank = 0; for (Double scoreField : scoreFields) { - if (scoreField>0.5 && scoreField > bestProb) { + if (scoreField > 0.5 && scoreField > bestProb) { String valueLicense = licenses.get(rank); valueLicense = valueLicense.replace("-", ""); license = License.valueOf(valueLicense.toUpperCase()); @@ -178,10 +180,10 @@ protected static List<CopyrightsLicense> extractResults(String copyrightOwnerAsJ entityRank++; } } - } catch(JsonProcessingException e) { + } catch (JsonProcessingException e) { LOGGER.error("failed to parse JSON copyrights/licenses classification result", e); } - + return results; } diff --git a/grobid-core/src/main/java/org/grobid/core/engines/ReferenceSegmenterParser.java b/grobid-core/src/main/java/org/grobid/core/engines/ReferenceSegmenterParser.java index 6a2d8e35b4..568e1c01a6 100644 --- a/grobid-core/src/main/java/org/grobid/core/engines/ReferenceSegmenterParser.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/ReferenceSegmenterParser.java @@ -3,16 +3,14 @@ import com.google.common.base.Function; import com.google.common.collect.Lists; import com.google.common.collect.Sets; -import org.grobid.core.GrobidModels; +import org.apache.commons.lang3.tuple.Pair; import org.grobid.core.document.Document; import org.grobid.core.document.DocumentPiece; import org.grobid.core.document.DocumentPointer; import org.grobid.core.engines.citations.LabeledReferenceResult; import org.grobid.core.engines.citations.ReferenceSegmenter; import org.grobid.core.engines.label.SegmentationLabels; -import org.grobid.core.engines.label.TaggingLabels; import org.grobid.core.engines.tagging.GenericTaggerUtils; -import org.grobid.core.engines.tagging.GrobidCRFEngine; import org.grobid.core.exceptions.GrobidException; import org.grobid.core.features.FeatureFactory; import org.grobid.core.features.FeaturesVectorReferenceSegmenter; @@ -21,232 +19,87 @@ import org.grobid.core.tokenization.LabeledTokensContainer; import org.grobid.core.tokenization.TaggingTokenSynchronizer; import org.grobid.core.utilities.BoundingBoxCalculator; -import org.grobid.core.utilities.GrobidProperties; import org.grobid.core.utilities.TextUtilities; import org.grobid.core.utilities.Triple; import org.slf4j.Logger; import org.slf4j.LoggerFactory; -import java.util.ArrayList; -import java.util.Collections; -import java.util.Iterator; -import java.util.List; -import java.util.SortedSet; +import java.util.*; import java.util.regex.Matcher; -import org.apache.commons.lang3.tuple.Pair; +import static org.grobid.core.GrobidModels.REFERENCE_SEGMENTER; public class ReferenceSegmenterParser extends AbstractParser implements ReferenceSegmenter { - private static final Logger LOGGER = LoggerFactory.getLogger(ReferenceSegmenterParser.class); + private static final Logger LOGGER = LoggerFactory.getLogger(ReferenceSegmenterParser.class); // projection scale for line length private static final int LINESCALE = 10; protected ReferenceSegmenterParser() { - super(GrobidModels.REFERENCE_SEGMENTER); + super(REFERENCE_SEGMENTER); } - @Override - public List<LabeledReferenceResult> extract(String referenceBlock) { - Document res = Document.createFromText(referenceBlock); + @Override + public List<LabeledReferenceResult> extract(String referenceBlock) { + Document res = Document.createFromText(referenceBlock); - DocumentPiece piece = new DocumentPiece( - new DocumentPointer(0, 0, 0), - new DocumentPointer(0, res.getTokenizations().size() - 1, res.getTokenizations().size() - 1)); + DocumentPiece piece = new DocumentPiece( + new DocumentPointer(0, 0, 0), + new DocumentPointer(0, res.getTokenizations().size() - 1, res.getTokenizations().size() - 1)); - return extract(res, Sets.newTreeSet(Collections.singletonList(piece)), false); - } + return extract(res, Sets.newTreeSet(Collections.singletonList(piece)), false); + } - /** + /** * * @param doc Document object - * @return <reference_label, reference_string> Note, that label is null when no label was detected - * example: <"[1]", "Hu W., Barkana, R., & Gruzinov A. Phys. Rev. Lett. 85, 1158"> + * @return <reference_label, reference_string> Note, that label is null when no + * label was detected + * example: <"[1]", "Hu W., Barkana, R., & Gruzinov A. Phys. Rev. + * Lett. 85, 1158"> */ - public List<LabeledReferenceResult> extract(Document doc) { - return extract(doc, false); - } - - public List<LabeledReferenceResult> extract(Document doc, boolean training) { - SortedSet<DocumentPiece> referencesParts = doc.getDocumentPart(SegmentationLabels.REFERENCES); - return extract(doc, referencesParts, training); - } - - public List<LabeledReferenceResult> extract(Document doc, SortedSet<DocumentPiece> referencesParts, boolean training) { - - Pair<String,List<LayoutToken>> featSeg = getReferencesSectionFeatured(doc, referencesParts); - String res; - List<LayoutToken> tokenizationsReferences; - if (featSeg == null) { - return null; - } - // if featSeg is null, it usually means that no reference segment is found in the - // document segmentation - String featureVector = featSeg.getLeft(); - tokenizationsReferences = featSeg.getRight(); - try { - - // to support long sequence in case of RNN usage we segment in pieces of less than the - // max_sequence_length and quite significantly overlapping - // this does not apply to CRF which can process "infinite" input sequence - // this is relevant to the reference segmenter RNN model, which is position-free in its - // application, but could not be generalized to other RNN or transformer model long inputs - if (GrobidProperties.getGrobidEngine(GrobidModels.REFERENCE_SEGMENTER) == GrobidCRFEngine.DELFT) { - String[] featureVectorLines = featureVector.split("\n"); - -/*for(LayoutToken token : tokenizationsReferences) { -System.out.print(token.getText()); -} -System.out.println("\n"); -System.out.println("total input lines: " + featureVectorLines.length + " - " + tokenizationsReferences.size() + " tokens");*/ - - int originalMaxSequence = 2000; - if (GrobidProperties.getInstance().getDelftRuntimeMaxSequenceLength(GrobidModels.REFERENCE_SEGMENTER.getModelName()) != -1) { - originalMaxSequence = GrobidProperties.getInstance().getDelftRuntimeMaxSequenceLength(GrobidModels.REFERENCE_SEGMENTER.getModelName()); - } - - if (featureVectorLines.length < originalMaxSequence || originalMaxSequence < 600) { - // if the input is lower than max sequence length, not need to segment - // if the max sequence length is too small, e.g. transformer, we won't be able to manage - // overlaps adapted to references - res = label(featureVector); - } else { - // we adjust max sequence value to take into account 500 token lines overlap - int maxSequence = Math.max(500, originalMaxSequence - 1000); - -//System.out.println("originalMaxSequence: " + originalMaxSequence + " / maxSequence adjusted to: " + maxSequence); - - List<List<String>> featureVectorPieces = new ArrayList<>(); - // segment the input vectors in overlapping sequences, according to the model max_sequence_length parameter - for(int i=0; (i*maxSequence) < featureVectorLines.length; i++) { - int lowerBound = i*maxSequence; - // overlapping: this localRes has 500 extra lines after the normal end - int upperBound = Math.min( ((i+1)*maxSequence)+500, featureVectorLines.length ); - if (featureVectorLines.length - lowerBound < originalMaxSequence) - upperBound = featureVectorLines.length; - -//System.out.println("lowerBound: " + lowerBound + " - upperBound: " + upperBound); - List<String> featureVectorPiece = new ArrayList<>(); - for(int j=lowerBound; j<upperBound; j++) - featureVectorPiece.add(featureVectorLines[j]); - featureVectorPieces.add(featureVectorPiece); - - if (upperBound == featureVectorLines.length) - break; - } - -/*System.out.println("featureVectorPieces.size(): " + featureVectorPieces.size()); -for(List<String> featureVectorPiece : featureVectorPieces) { -System.out.println(featureVectorPiece.size()); -}*/ - // label every pieces in batch - List<String> allRes = new ArrayList<>(); - List<String> allVectors = new ArrayList<>(); - for(List<String> featureVectorPiece : featureVectorPieces) { - StringBuilder localFeatureVector = new StringBuilder(); - for(int j=0; j<featureVectorPiece.size(); j++) { - localFeatureVector.append(featureVectorPiece.get(j)).append("\n"); - } - allVectors.add(localFeatureVector.toString()); - } - - // parallel labeling of the input segments - String fullRes = label(allVectors); - - // segment this result to get back the input chunk alignment (with extra 500 overlaping lines) - String[] fullResLines = fullRes.split("\n"); - int pos = 0; - for(List<String> featureVectorPiece : featureVectorPieces) { - StringBuilder localRes = new StringBuilder(); - int localSize = featureVectorPiece.size(); - for(int i=pos; i<pos+localSize; i++) { - localRes.append(fullResLines[i]).append("\n"); - } - allRes.add(localRes.toString()); - pos += localSize; - } - - // combine results and reconnect smoothly overlaps - StringBuilder resBuilder = new StringBuilder(); - int previousTransitionPos = 0; - for(int i=0; i<allRes.size(); i++) { - String localRes = allRes.get(i); - String[] localResLines = localRes.split("\n"); -//System.out.println("localResLines.length: " + localResLines.length); - int transitionPos = localResLines.length; - if (i != allRes.size()-1) { - // in the trailing redundant part (500 last lines), we identify the line index - // of the last "closing" label, this is the point where we will reconnect the - // labeled segments to avoid breaking a labeled field - - for(int k=localResLines.length-1; k>=0; k--) { - if (localResLines.length-k == 500) { - // this is the max overlap, we don't go beyond! - transitionPos = k; - break; - } - - String line = localResLines[k]; - if (line.endsWith(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<label>") || - line.endsWith(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<reference>")) { - // we can stop the line before this one - transitionPos = k; - break; - } - } - } - // else: we are at the last chunk, so we take the content until the very end - -//System.out.println("previousTransitionPos: " + previousTransitionPos); -//System.out.println("transitionPos: " + transitionPos + "\n"); - - List<String> selectedlocalResLines = new ArrayList<>(); - for(int j= previousTransitionPos; j<transitionPos; j++) { - if (j == previousTransitionPos && previousTransitionPos != 0) { - // we want to be sure to have a starting label - String localLine = localResLines[j]; - if (localLine.indexOf(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX) == -1) { - localLine = localLine.replace("<label>", TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<label>"); - localLine = localLine.replace("<reference>", TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<reference>"); - } - selectedlocalResLines.add(localLine); - } else if (j == previousTransitionPos && previousTransitionPos == 0 && i != 0) { - // previousTransitionPos is 0 and we are not at the first segment: we had a non overlapping - // transition, we might want to avoid a starting label at this point - String localLine = localResLines[j]; - if (localLine.indexOf(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX) != -1) { - localLine = localLine.replace(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<label>", "<label>"); - localLine = localLine.replace(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX+"<reference>", "<reference>"); - } - selectedlocalResLines.add(localLine); - } else { - selectedlocalResLines.add(localResLines[j]); - } - } - for(String localResLine : selectedlocalResLines) - resBuilder.append(localResLine).append("\n"); - - previousTransitionPos = transitionPos-maxSequence; - } - res = resBuilder.toString(); - } - } else - res = label(featureVector); - } - catch(Exception e) { - throw new GrobidException("Labeling in ReferenceSegmenter fails.", e); - } - if (res == null) { - return null; - } - - // if we extract for generating training data, we also give back the used features + public List<LabeledReferenceResult> extract(Document doc) { + return extract(doc, false); + } + + public List<LabeledReferenceResult> extract(Document doc, boolean training) { + SortedSet<DocumentPiece> referencesParts = doc.getDocumentPart(SegmentationLabels.REFERENCES); + return extract(doc, referencesParts, training); + } + + public List<LabeledReferenceResult> extract(Document doc, SortedSet<DocumentPiece> referencesParts, + boolean training) { + + Pair<String, List<LayoutToken>> featSeg = getReferencesSectionFeatured(doc, referencesParts); + String res; + List<LayoutToken> tokenizationsReferences; + if (featSeg == null) { + return null; + } + // if featSeg is null, it usually means that no reference segment is found in + // the document segmentation + String featureVector = featSeg.getLeft(); + tokenizationsReferences = featSeg.getRight(); + try { + res = label(featureVector); + } catch (Exception e) { + throw new GrobidException("Labeling in ReferenceSegmenter fails.", e); + } + if (res == null) { + return null; + } + + // if we extract for generating training data, we also give back the used + // features List<Triple<String, String, String>> labeled = GenericTaggerUtils.getTokensWithLabelsAndFeatures(res, training); return getExtractionResult(tokenizationsReferences, labeled); } - private List<LabeledReferenceResult> getExtractionResult(List<LayoutToken> tokenizations, List<Triple<String, String, String>> labeled) { + private List<LabeledReferenceResult> getExtractionResult( + List<LayoutToken> tokenizations, + List<Triple<String, String, String>> labeled + ) { final List<LabeledReferenceResult> resultList = new ArrayList<>(); final StringBuilder reference = new StringBuilder(); final List<LayoutToken> referenceTokens = new ArrayList<>(); @@ -255,23 +108,22 @@ private List<LabeledReferenceResult> getExtractionResult(List<LayoutToken> token TaggingTokenSynchronizer synchronizer = new TaggingTokenSynchronizer(null, labeled, tokenizations); - Function<LabeledTokensContainer, Void> function = new Function<LabeledTokensContainer, Void>() { - @Override public Void apply(LabeledTokensContainer container) { - features.append(container.getFeatureString()); - features.append('\n'); - if (container.isBeginning()) { - if (reference.length() != 0) { - resultList.add(new LabeledReferenceResult(referenceLabel.length() == 0 ? null : - referenceLabel.toString().trim(), reference.toString().trim(), Lists.newArrayList(referenceTokens), - features.toString(), BoundingBoxCalculator.calculate(referenceTokens))); - reference.setLength(0); - referenceLabel.setLength(0); - features.setLength(0); - referenceTokens.clear(); - } + Function<LabeledTokensContainer, Void> function = container -> { + features.append(container.getFeatureString()); + features.append('\n'); + if (container.isBeginning()) { + if (reference.length() != 0) { + resultList.add(new LabeledReferenceResult( + referenceLabel.length() == 0 ? null : referenceLabel.toString().trim(), + reference.toString().trim(), Lists.newArrayList(referenceTokens), + features.toString(), BoundingBoxCalculator.calculate(referenceTokens))); + reference.setLength(0); + referenceLabel.setLength(0); + features.setLength(0); + referenceTokens.clear(); } - return null; } + return null; }; Iterator<LabeledTokensContainer> iterator = synchronizer.iterator(); @@ -306,8 +158,9 @@ private List<LabeledReferenceResult> getExtractionResult(List<LayoutToken> token // Handle last one. if (!iterator.hasNext()) { - resultList.add(new LabeledReferenceResult(referenceLabel.length() == 0 ? null : - referenceLabel.toString().trim(), reference.toString().trim(), + resultList.add(new LabeledReferenceResult( + referenceLabel.length() == 0 ? null : referenceLabel.toString().trim(), + reference.toString().trim(), referenceTokens, features.toString(), BoundingBoxCalculator.calculate(referenceTokens))); reference.setLength(0); @@ -318,190 +171,184 @@ private List<LabeledReferenceResult> getExtractionResult(List<LayoutToken> token return resultList; } - public Pair<String,String> createTrainingData(Document doc, int id) { - SortedSet<DocumentPiece> referencesParts = doc.getDocumentPart(SegmentationLabels.REFERENCES); - Pair<String,List<LayoutToken>> featSeg = getReferencesSectionFeatured(doc, referencesParts); - String res; - List<LayoutToken> tokenizations; - if (featSeg == null) { - return null; - } - // if featSeg is null, it usually means that no reference segment is found in the - // document segmentation - String featureVector = featSeg.getLeft(); - tokenizations = featSeg.getRight(); - try { - res = label(featureVector); - } - catch(Exception e) { - throw new GrobidException("Sequence labeling in ReferenceSegmenter fails.", e); - } - if (res == null) { - return null; - } + public Pair<String, String> createTrainingData(Document doc, int id) { + SortedSet<DocumentPiece> referencesParts = doc.getDocumentPart(SegmentationLabels.REFERENCES); + Pair<String, List<LayoutToken>> featSeg = getReferencesSectionFeatured(doc, referencesParts); + String res; + List<LayoutToken> tokenizations; + if (featSeg == null) { + return null; + } + // if featSeg is null, it usually means that no reference segment is found in + // the + // document segmentation + String featureVector = featSeg.getLeft(); + tokenizations = featSeg.getRight(); + try { + res = label(featureVector); + } catch (Exception e) { + throw new GrobidException("Sequence labeling in ReferenceSegmenter fails.", e); + } + if (res == null) { + return null; + } List<Pair<String, String>> labeled = GenericTaggerUtils.getTokensAndLabels(res); StringBuilder sb = new StringBuilder(); - //noinspection StringConcatenationInsideStringBufferAppend - sb.append("<tei xml:space=\"preserve\">\n" + - " <teiHeader>\n" + - " <fileDesc xml:id=\"_" + id + "\"/>\n" + - " </teiHeader>\n" + - " <text xml:lang=\"en\">\n" + - " <listBibl>\n"); - - int tokPtr = 0; - boolean addSpace = false; - boolean addEOL = false; - String lastTag = null; - boolean refOpen = false; - for (Pair<String, String> l : labeled) { + // noinspection StringConcatenationInsideStringBufferAppend + sb.append("<tei xml:space=\"preserve\">\n" + + " <teiHeader>\n" + + " <fileDesc xml:id=\"_" + id + "\"/>\n" + + " </teiHeader>\n" + + " <text xml:lang=\"en\">\n" + + " <listBibl>\n"); + + int tokPtr = 0; + boolean addSpace = false; + boolean addEOL = false; + String lastTag = null; + boolean refOpen = false; + for (Pair<String, String> l : labeled) { String tok = l.getLeft(); String label = l.getRight(); - int tokPtr2 = tokPtr; - for(; tokPtr2 < tokenizations.size(); tokPtr2++) { + int tokPtr2 = tokPtr; + for (; tokPtr2 < tokenizations.size(); tokPtr2++) { if (tokenizations.get(tokPtr2).t().equals(" ")) { - addSpace = true; - } - else if (tokenizations.get(tokPtr2).t().equals("\n") || - tokenizations.get(tokPtr).t().equals("\r") ) { - addEOL = true; - } - else { - break; - } + addSpace = true; + } else if (tokenizations.get(tokPtr2).t().equals("\n") || + tokenizations.get(tokPtr).t().equals("\r")) { + addEOL = true; + } else { + break; + } } - tokPtr = tokPtr2; + tokPtr = tokPtr2; if (tokPtr >= tokenizations.size()) { - LOGGER.error("Implementation error: Reached the end of tokenizations, but current token is " + tok); - // we add a space to avoid concatenated text - addSpace = true; + LOGGER.error("Implementation error: Reached the end of tokenizations, but current token is " + tok); + // we add a space to avoid concatenated text + addSpace = true; + } else { + String tokenizationToken = tokenizations.get(tokPtr).getText(); + + if ((tokPtr != tokenizations.size()) && !tokenizationToken.equals(tok)) { + // and we add a space by default to avoid concatenated text + addSpace = true; + if (!tok.startsWith(tokenizationToken)) { + // this is a very exceptional case due to a sequence of accent/diacresis, in + // this case we skip + // a shift in the tokenizations list and continue on the basis of the labeled + // token + // we check one ahead + tokPtr++; + tokenizationToken = tokenizations.get(tokPtr).getText(); + if (!tok.equals(tokenizationToken)) { + // we try another position forward (second hope!) + tokPtr++; + tokenizationToken = tokenizations.get(tokPtr).getText(); + if (!tok.equals(tokenizationToken)) { + // we try another position forward (last hope!) + tokPtr++; + tokenizationToken = tokenizations.get(tokPtr).getText(); + if (!tok.equals(tokenizationToken)) { + // we return to the initial position + tokPtr = tokPtr - 3; + tokenizationToken = tokenizations.get(tokPtr).getText(); + LOGGER.error("Implementation error, tokens out of sync: " + + tokenizationToken + " != " + tok + ", at position " + tokPtr); + } + } + } + } + // note: if the above condition is true, this is an exceptional case due to a + // sequence of accent/diacresis and we can go on as a full string match + } } - else { - String tokenizationToken = tokenizations.get(tokPtr).getText(); - - if ((tokPtr != tokenizations.size()) && !tokenizationToken.equals(tok)) { - // and we add a space by default to avoid concatenated text - addSpace = true; - if (!tok.startsWith(tokenizationToken)) { - // this is a very exceptional case due to a sequence of accent/diacresis, in this case we skip - // a shift in the tokenizations list and continue on the basis of the labeled token - // we check one ahead - tokPtr++; - tokenizationToken = tokenizations.get(tokPtr).getText(); - if (!tok.equals(tokenizationToken)) { - // we try another position forward (second hope!) - tokPtr++; - tokenizationToken = tokenizations.get(tokPtr).getText(); - if (!tok.equals(tokenizationToken)) { - // we try another position forward (last hope!) - tokPtr++; - tokenizationToken = tokenizations.get(tokPtr).getText(); - if (!tok.equals(tokenizationToken)) { - // we return to the initial position - tokPtr = tokPtr-3; - tokenizationToken = tokenizations.get(tokPtr).getText(); - LOGGER.error("Implementation error, tokens out of sync: " + - tokenizationToken + " != " + tok + ", at position " + tokPtr); - } - } - } - } - // note: if the above condition is true, this is an exceptional case due to a - // sequence of accent/diacresis and we can go on as a full string match - } - } - - String plainLabel = GenericTaggerUtils.getPlainLabel(label); - - boolean tagClosed = (lastTag != null) && testClosingTag(sb, label, lastTag, addSpace, addEOL); - - if (tagClosed) { - addSpace = false; - addEOL = false; - } - if (tagClosed && lastTag.equals("<reference>")) { - refOpen = false; - } - String output; - String field; - if (refOpen) { - field = "<label>"; - } - else { - field = "<bibl><label>"; - } - output = writeField(label, lastTag, tok, "<label>", field, addSpace, addEOL, 2); - if (output != null) { - sb.append(output); - refOpen = true; - } - else { - if (refOpen) { - field = ""; - } - else { - field = "<bibl>"; - } - output = writeField(label, lastTag, tok, "<reference>", field, addSpace, addEOL, 2); - if (output != null) { - sb.append(output); - refOpen= true; - } - else { - output = writeField(label, lastTag, tok, "<other>", "", addSpace, addEOL, 2); - if (output != null) { - sb.append(output); - refOpen = false; - } - } - } - - lastTag = plainLabel; - addSpace = false; - addEOL = false; + + String plainLabel = GenericTaggerUtils.getPlainLabel(label); + + boolean tagClosed = (lastTag != null) && testClosingTag(sb, label, lastTag, addSpace, addEOL); + + if (tagClosed) { + addSpace = false; + addEOL = false; + } + if (tagClosed && lastTag.equals("<reference>")) { + refOpen = false; + } + String output; + String field; + if (refOpen) { + field = "<label>"; + } else { + field = "<bibl><label>"; + } + output = writeField(label, lastTag, tok, "<label>", field, addSpace, addEOL, 2); + if (output != null) { + sb.append(output); + refOpen = true; + } else { + if (refOpen) { + field = ""; + } else { + field = "<bibl>"; + } + output = writeField(label, lastTag, tok, "<reference>", field, addSpace, addEOL, 2); + if (output != null) { + sb.append(output); + refOpen = true; + } else { + output = writeField(label, lastTag, tok, "<other>", "", addSpace, addEOL, 2); + if (output != null) { + sb.append(output); + refOpen = false; + } + } + } + + lastTag = plainLabel; + addSpace = false; + addEOL = false; tokPtr++; } - if (refOpen) { - sb.append("</bibl>"); - } + if (refOpen) { + sb.append("</bibl>"); + } sb.append("\n </listBibl>\n" + - " </text>\n" + - "</tei>\n"); + " </text>\n" + + "</tei>\n"); - return Pair.of(sb.toString(), featureVector); + return Pair.of(sb.toString(), featureVector); } - - private boolean testClosingTag(StringBuilder buffer, + private boolean testClosingTag(StringBuilder buffer, String currentTag, String lastTag, - boolean addSpace, - boolean addEOL) { + boolean addSpace, + boolean addEOL) { boolean res = false; if (!currentTag.equals(lastTag)) { res = true; // we close the current tag if (lastTag.equals("<other>")) { - if (addEOL) + if (addEOL) buffer.append("<lb/>"); - if (addSpace) + if (addSpace) buffer.append(" "); buffer.append("\n"); } else if (lastTag.equals("<label>")) { - buffer.append("</label>"); - if (addEOL) + buffer.append("</label>"); + if (addEOL) buffer.append("<lb/>"); - if (addSpace) + if (addSpace) buffer.append(" "); } else if (lastTag.equals("<reference>")) { - if (addEOL) + if (addEOL) buffer.append("<lb/>"); - if (addSpace) + if (addSpace) buffer.append(" "); buffer.append("</bibl>\n"); } else { @@ -517,42 +364,40 @@ private String writeField(String currentTag, String field, String outField, boolean addSpace, - boolean addEOL, - int nbIndent) { + boolean addEOL, + int nbIndent) { String result = null; if (currentTag.endsWith(field)) { if (currentTag.endsWith("<other>")) { result = ""; - if (currentTag.equals("I-<other>")) { - result += "\n"; - for (int i = 0; i < nbIndent; i++) { - result += " "; - } - } - if (addEOL) + if (currentTag.equals("I-<other>")) { + result += "\n"; + for (int i = 0; i < nbIndent; i++) { + result += " "; + } + } + if (addEOL) result += "<lb/>"; - if (addSpace) + if (addSpace) result += " "; result += TextUtilities.HTMLEncode(token); - } - else if ((lastTag != null) && currentTag.endsWith(lastTag)) { + } else if ((lastTag != null) && currentTag.endsWith(lastTag)) { result = ""; - if (addEOL) + if (addEOL) result += "<lb/>"; - if (addSpace) + if (addSpace) result += " "; - if (currentTag.startsWith("I-")) - result += outField; + if (currentTag.startsWith("I-")) + result += outField; result += TextUtilities.HTMLEncode(token); - } - else { + } else { result = ""; - if (outField.length() > 0) { - for (int i = 0; i < nbIndent; i++) { - result += " "; - } - } - if (addEOL) + if (outField.length() > 0) { + for (int i = 0; i < nbIndent; i++) { + result += " "; + } + } + if (addEOL) result += "<lb/>"; if (addSpace) result += " "; @@ -562,138 +407,136 @@ else if ((lastTag != null) && currentTag.endsWith(lastTag)) { return result; } - static public Pair<String,List<LayoutToken>> getReferencesSectionFeatured(Document doc, - SortedSet<DocumentPiece> referencesParts) { - if ((referencesParts == null) || (referencesParts.size() == 0)) { - return null; - } - FeatureFactory featureFactory = FeatureFactory.getInstance(); - List<Block> blocks = doc.getBlocks(); - if ( (blocks == null) || blocks.size() == 0) { - return null; - } - - StringBuilder citations = new StringBuilder(); + static public Pair<String, List<LayoutToken>> getReferencesSectionFeatured(Document doc, + SortedSet<DocumentPiece> referencesParts) { + if ((referencesParts == null) || (referencesParts.size() == 0)) { + return null; + } + FeatureFactory featureFactory = FeatureFactory.getInstance(); + List<Block> blocks = doc.getBlocks(); + if ((blocks == null) || blocks.size() == 0) { + return null; + } + + StringBuilder citations = new StringBuilder(); boolean newline; int n; // overall token number - FeaturesVectorReferenceSegmenter features; - FeaturesVectorReferenceSegmenter previousFeatures = null; - boolean endblock; - boolean startblock; - //int mm = 0; // token position in the sentence + FeaturesVectorReferenceSegmenter features; + FeaturesVectorReferenceSegmenter previousFeatures = null; + boolean endblock; + boolean startblock; + // int mm = 0; // token position in the sentence int nn; // token position in the line - double lineStartX = Double.NaN; - boolean indented = false; + double lineStartX = Double.NaN; + boolean indented = false; - List<LayoutToken> tokenizationsReferences = new ArrayList<LayoutToken>(); - List<LayoutToken> tokenizations = doc.getTokenizations(); + List<LayoutToken> tokenizationsReferences = new ArrayList<LayoutToken>(); + List<LayoutToken> tokenizations = doc.getTokenizations(); - int maxLineLength = 1; - //List<Integer> lineLengths = new ArrayList<Integer>(); - int currentLineLength = 0; - //int lineIndex = 0; + int maxLineLength = 1; + // List<Integer> lineLengths = new ArrayList<Integer>(); + int currentLineLength = 0; + // int lineIndex = 0; - // we calculate current max line length and intialize the body tokenization structure - for(DocumentPiece docPiece : referencesParts) { - DocumentPointer dp1 = docPiece.getLeft(); - DocumentPointer dp2 = docPiece.getRight(); + // we calculate current max line length and intialize the body tokenization + // structure + for (DocumentPiece docPiece : referencesParts) { + DocumentPointer dp1 = docPiece.getLeft(); + DocumentPointer dp2 = docPiece.getRight(); int tokens = dp1.getTokenDocPos(); int tokene = dp2.getTokenDocPos(); for (int i = tokens; i <= tokene; i++) { tokenizationsReferences.add(tokenizations.get(i)); - currentLineLength += tokenizations.get(i).getText().length(); - if (tokenizations.get(i).t().equals("\n") || tokenizations.get(i).t().equals("\r") ) { - //lineLengths.add(currentLineLength); - if (currentLineLength > maxLineLength) - maxLineLength = currentLineLength; - currentLineLength = 0; - } + currentLineLength += tokenizations.get(i).getText().length(); + if (tokenizations.get(i).t().equals("\n") || tokenizations.get(i).t().equals("\r")) { + // lineLengths.add(currentLineLength); + if (currentLineLength > maxLineLength) + maxLineLength = currentLineLength; + currentLineLength = 0; + } } - } - - for(DocumentPiece docPiece : referencesParts) { - DocumentPointer dp1 = docPiece.getLeft(); - DocumentPointer dp2 = docPiece.getRight(); - -/*for(int i=dp1.getTokenDocPos(); i<dp2.getTokenDocPos(); i++) { - System.out.print(tokenizations.get(i)); -} -System.out.println(""); -*/ - //currentLineLength = lineLengths.get(lineIndex); - nn = 0; - int tokenIndex = 0; - int blockIndex = dp1.getBlockPtr(); - Block block = null; - List<LayoutToken> tokens; - boolean previousNewline = true; - currentLineLength = 0; - String currentLineProfile = null; + } + + for (DocumentPiece docPiece : referencesParts) { + DocumentPointer dp1 = docPiece.getLeft(); + DocumentPointer dp2 = docPiece.getRight(); + + /* + * for(int i=dp1.getTokenDocPos(); i<dp2.getTokenDocPos(); i++) { + * System.out.print(tokenizations.get(i)); + * } + * System.out.println(""); + */ + // currentLineLength = lineLengths.get(lineIndex); + nn = 0; + int tokenIndex = 0; + int blockIndex = dp1.getBlockPtr(); + Block block = null; + List<LayoutToken> tokens; + boolean previousNewline = true; + currentLineLength = 0; + String currentLineProfile = null; for (n = dp1.getTokenDocPos(); n <= dp2.getTokenDocPos(); n++) { String text = tokenizations.get(n).getText(); - if (text == null) { - continue; - } - - // set corresponding block - if ( (block != null) && (n > block.getEndToken()) ) { - blockIndex++; - tokenIndex = 0; - currentLineLength = 0; - currentLineProfile = null; - } - - if (blockIndex<blocks.size()) { - block = blocks.get(blockIndex); - if (n == block.getStartToken()) { - startblock = true; - endblock = false; - } - else if (n == block.getEndToken()) { - startblock = false; - endblock = true; - } - else { - startblock = false; - endblock = false; - } - } - else { - block = null; - startblock = false; - endblock = false; - } - // set corresponding token - if (block != null) - tokens = block.getTokens(); - else - tokens = null; - - if (text.equals("\n") || text.equals("\r")) { - previousNewline = true; - nn = 0; - currentLineLength = 0; - currentLineProfile = null; - //lineIndex++; - //currentLineLength = lineLengths.get(lineIndex); + if (text == null) { continue; } - else { + + // set corresponding block + if ((block != null) && (n > block.getEndToken())) { + blockIndex++; + tokenIndex = 0; + currentLineLength = 0; + currentLineProfile = null; + } + + if (blockIndex < blocks.size()) { + block = blocks.get(blockIndex); + if (n == block.getStartToken()) { + startblock = true; + endblock = false; + } else if (n == block.getEndToken()) { + startblock = false; + endblock = true; + } else { + startblock = false; + endblock = false; + } + } else { + block = null; + startblock = false; + endblock = false; + } + // set corresponding token + if (block != null) + tokens = block.getTokens(); + else + tokens = null; + + if (text.equals("\n") || text.equals("\r")) { + previousNewline = true; + nn = 0; + currentLineLength = 0; + currentLineProfile = null; + // lineIndex++; + // currentLineLength = lineLengths.get(lineIndex); + continue; + } else { newline = false; - nn += text.length(); // +1 for segmentation symbol - } + nn += text.length(); // +1 for segmentation symbol + } - if (text.equals(" ") || text.equals("\t")) { + if (text.equals(" ") || text.equals("\t")) { nn++; continue; - } + } - if (text.trim().length() == 0) { - continue; - } + if (text.trim().length() == 0) { + continue; + } LayoutToken token = null; if (tokens != null) { @@ -711,23 +554,25 @@ else if (n == block.getEndToken()) { if (previousNewline) { newline = true; previousNewline = false; - if (token != null && previousFeatures != null) { - double previousLineStartX = lineStartX; + if (token != null && previousFeatures != null) { + double previousLineStartX = lineStartX; lineStartX = token.getX(); double characterWidth = token.width / token.getText().length(); - if (!Double.isNaN(previousLineStartX)) { - // Indentation if line start is > 1 character width to the right of previous line start + if (!Double.isNaN(previousLineStartX)) { + // Indentation if line start is > 1 character width to the right of previous + // line start if (lineStartX - previousLineStartX > characterWidth) - indented = true; - // Indentation ends if line start is > 1 character width to the left of previous line start + indented = true; + // Indentation ends if line start is > 1 character width to the left of previous + // line start else if (previousLineStartX - lineStartX > characterWidth) indented = false; // Otherwise indentation is unchanged - } - } + } + } } - if (TextUtilities.filterLine(text)) { + if (TextUtilities.filterLine(text)) { continue; } @@ -762,53 +607,50 @@ else if (previousLineStartX - lineStartX > characterWidth) } - if ( (n == 0) || (previousNewline) ) { + if ((n == 0) || (previousNewline)) { features.lineStatus = "LINESTART"; - if (n == 0) - features.blockStatus = "BLOCKSTART"; - nn = 0; + if (n == 0) + features.blockStatus = "BLOCKSTART"; + nn = 0; } if (indented) { - features.alignmentStatus = "LINEINDENT"; - } - else { - features.alignmentStatus = "ALIGNEDLEFT"; + features.alignmentStatus = "LINEINDENT"; + } else { + features.alignmentStatus = "ALIGNEDLEFT"; } - { + { // look ahead... boolean endline = true; int ii = 1; boolean endloop = false; - String accumulated = text; + String accumulated = text; while ((n + ii < tokenizations.size()) && (!endloop)) { String tok = tokenizations.get(n + ii).getText(); if (tok != null) { - if (currentLineProfile == null) - accumulated += tok; + if (currentLineProfile == null) + accumulated += tok; if (tok.equals("\n") || tok.equals("\r")) { endloop = true; - if (currentLineLength ==0) { - currentLineLength = accumulated.length(); - } - if (currentLineProfile == null) { - currentLineProfile = TextUtilities.punctuationProfile(accumulated); - } - } - else if (!tok.equals(" ") && !tok.equals("\t")) { - endline = false; - } - else { + if (currentLineLength == 0) { + currentLineLength = accumulated.length(); + } + if (currentLineProfile == null) { + currentLineProfile = TextUtilities.punctuationProfile(accumulated); + } + } else if (!tok.equals(" ") && !tok.equals("\t")) { + endline = false; + } else { if (TextUtilities.filterLine(tok)) { endloop = true; - if (currentLineLength ==0) { - currentLineLength = accumulated.length(); - } - if (currentLineProfile == null) { - currentLineProfile = TextUtilities.punctuationProfile(accumulated); - } + if (currentLineLength == 0) { + currentLineLength = accumulated.length(); + } + if (currentLineProfile == null) { + currentLineProfile = TextUtilities.punctuationProfile(accumulated); + } } } } @@ -818,23 +660,22 @@ else if (!tok.equals(" ") && !tok.equals("\t")) { endline = true; } - if (endline && (block != null) && (n+ii == block.getEndToken())) { - endblock = true; - } + if (endline && (block != null) && (n + ii == block.getEndToken())) { + endblock = true; + } ii++; } if ((!endline) && !(newline)) { features.lineStatus = "LINEIN"; - } - else if (!newline) { + } else if (!newline) { features.lineStatus = "LINEEND"; previousNewline = true; } - if (startblock) { - features.blockStatus = "BLOCKSTART"; - } + if (startblock) { + features.blockStatus = "BLOCKSTART"; + } if ((!endblock) && (features.blockStatus == null)) features.blockStatus = "BLOCKIN"; else if (features.blockStatus == null) { @@ -890,10 +731,10 @@ else if (features.blockStatus == null) { features.http = true; } - if ( (token != null) && (token.isBold()) ) + if ((token != null) && (token.isBold())) features.bold = true; - if ( (token != null) && (token.isItalic()) ) + if ((token != null) && (token.isItalic())) features.italic = true; if (features.capitalisation == null) @@ -904,24 +745,24 @@ else if (features.blockStatus == null) { if (features.punctType == null) features.punctType = "NOPUNCT"; -//System.out.println(nn + "\t" + currentLineLength + "\t" + maxLineLength); + // System.out.println(nn + "\t" + currentLineLength + "\t" + maxLineLength); features.lineLength = featureFactory - .linearScaling(currentLineLength, maxLineLength, LINESCALE); + .linearScaling(currentLineLength, maxLineLength, LINESCALE); - features.relativePosition = featureFactory - .linearScaling(nn, currentLineLength, LINESCALE); + features.relativePosition = featureFactory + .linearScaling(nn, currentLineLength, LINESCALE); - features.punctuationProfile = currentLineProfile; + features.punctuationProfile = currentLineProfile; if (previousFeatures != null) citations.append(previousFeatures.printVector()); - //mm++; + // mm++; previousFeatures = features; - } - } - if (previousFeatures != null) - citations.append(previousFeatures.printVector()); + } + } + if (previousFeatures != null) + citations.append(previousFeatures.printVector()); - return Pair.of(citations.toString(), tokenizationsReferences); - } + return Pair.of(citations.toString(), tokenizationsReferences); + } } diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/ClassifierFactory.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/ClassifierFactory.java new file mode 100644 index 0000000000..06a9c42b5a --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/ClassifierFactory.java @@ -0,0 +1,99 @@ +package org.grobid.core.engines.tagging; + +import org.grobid.core.engines.tagging.delft.OnnxClassificationModel; +import org.grobid.core.jni.DeLFTClassifierModel; +import org.grobid.core.utilities.GrobidProperties; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.File; +import java.nio.file.Path; +import java.util.HashMap; +import java.util.Map; + +/** + * Factory for text classification models. + * + * Supports both JEP-based DeLFT classifiers and ONNX-based classifiers. + * The engine is selected based on grobid.yaml configuration. + */ +public class ClassifierFactory { + + private static final Logger LOGGER = LoggerFactory.getLogger(ClassifierFactory.class); + + private static Map<String, GenericClassifier> cache = new HashMap<>(); + + private ClassifierFactory() { + } + + /** + * Get a classifier for the given model name. + * + * @param modelName The model name (e.g., "copyright", "license") + * @return A GenericClassifier instance + */ + public static synchronized GenericClassifier getClassifier(String modelName) { + GrobidCRFEngine engine = GrobidProperties.getGrobidEngine(modelName); + String architecture; + if (engine == GrobidCRFEngine.ONNX) { + architecture = GrobidProperties.getOnnxArchitecture(modelName); + } else { + architecture = GrobidProperties.getDelftArchitecture(modelName); + } + return getClassifier(modelName, architecture); + } + + /** + * Get a classifier for the given model name and architecture. + * + * @param modelName The model name (e.g., "copyright", "license") + * @param architecture The DeLFT architecture (e.g., "gru") + * @return A GenericClassifier instance + */ + public static synchronized GenericClassifier getClassifier(String modelName, String architecture) { + GenericClassifier classifier = cache.get(modelName); + if (classifier == null) { + GrobidCRFEngine engine = GrobidProperties.getGrobidEngine(modelName); + + if (engine == null) { + throw new IllegalStateException("No engine configured for model: " + modelName); + } + + switch (engine) { + case DELFT: + LOGGER.info("Creating DeLFT classifier for model: {}", modelName); + classifier = new DeLFTClassifierModel(modelName, architecture); + break; + case ONNX: + LOGGER.info("Creating ONNX classifier for model: {}", modelName); + try { + // Model path: {grobid-home}/models/{modelName}-{architecture}.onnx/ + File modelPath = GrobidProperties.getModelPath(); + Path modelDir = modelPath.toPath().resolve(modelName + "-" + architecture + ".onnx"); + classifier = new OnnxClassificationModel(modelDir); + } catch (Exception e) { + throw new RuntimeException("Failed to load ONNX classification model: " + modelName, e); + } + break; + default: + throw new IllegalStateException("Unsupported engine for classification: " + engine); + } + cache.put(modelName, classifier); + } + return classifier; + } + + /** + * Clear the classifier cache. + */ + public static synchronized void clearCache() { + for (GenericClassifier classifier : cache.values()) { + try { + classifier.close(); + } catch (Exception e) { + LOGGER.warn("Error closing classifier", e); + } + } + cache.clear(); + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/GenericClassifier.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/GenericClassifier.java new file mode 100644 index 0000000000..0ab27d5f53 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/GenericClassifier.java @@ -0,0 +1,19 @@ +package org.grobid.core.engines.tagging; + +import java.io.Closeable; +import java.util.List; + +/** + * Common interface for text classification models. + * Supports both JEP-based DeLFT classifiers and ONNX-based classifiers. + */ +public interface GenericClassifier extends Closeable { + + /** + * Classify texts in batch. + * + * @param texts List of texts to classify + * @return JSON string with classification results in DeLFT format + */ + String classify(List<String> texts) throws Exception; +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/GrobidCRFEngine.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/GrobidCRFEngine.java index 0c0014a4c8..28ce7998ff 100644 --- a/grobid-core/src/main/java/org/grobid/core/engines/tagging/GrobidCRFEngine.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/GrobidCRFEngine.java @@ -3,12 +3,13 @@ import java.util.Arrays; /** - * Sequence labeling engine in GROBID + * Sequence labeling engine in GROBID */ public enum GrobidCRFEngine { WAPITI("wapiti"), CRFPP("crf"), DELFT("delft"), + ONNX("onnx"), DUMMY("dummy"); private final String ext; @@ -36,5 +37,4 @@ public static GrobidCRFEngine get(String name) { "', possible values are: " + Arrays.toString(values())); } - } diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/OnnxTagger.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/OnnxTagger.java new file mode 100644 index 0000000000..5ce2f12b9a --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/OnnxTagger.java @@ -0,0 +1,68 @@ +package org.grobid.core.engines.tagging; + +import com.google.common.base.Joiner; +import org.grobid.core.GrobidModel; +import org.grobid.core.engines.tagging.delft.OnnxSequenceLabellingModel; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.File; +import java.io.IOException; + +/** + * ONNX-based tagger for sequence labeling. + * Uses DeLFT models exported to ONNX format with CRF decoding in pure Java. + * + * This tagger provides a pure Java alternative to the DeLFT tagger, which + * requires + * Python/JEP at runtime. ONNX models are loaded from directories with the + * naming + * convention: {model-name}-{architecture}.onnx + */ +public class OnnxTagger implements GenericTagger { + + private static final Logger LOGGER = LoggerFactory.getLogger(OnnxTagger.class); + + private final OnnxSequenceLabellingModel model; + private final GrobidModel grobidModel; + + /** + * Create an ONNX tagger for the given model. + * + * @param grobidModel The GROBID model to use + * @param architecture The DeLFT architecture (e.g., "BidLSTM_CRF_FEATURES") - + * not used, included for API compatibility + */ + public OnnxTagger(GrobidModel grobidModel, String architecture) { + this.grobidModel = grobidModel; + + // Model path is now correctly resolved by GrobidProperties.getModelPath() for + // ONNX engine + File modelDir = new File(grobidModel.getModelPath()); + + LOGGER.info("Loading ONNX model from: {}", modelDir); + + try { + this.model = new OnnxSequenceLabellingModel(modelDir.toPath()); + } catch (Exception e) { + throw new RuntimeException("Failed to load ONNX model: " + modelDir, e); + } + } + + @Override + public String label(Iterable<String> data) { + return label(Joiner.on('\n').join(data)); + } + + @Override + public String label(String data) { + return model.labelGrobidInput(data); + } + + @Override + public void close() throws IOException { + if (model != null) { + model.close(); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/TaggerFactory.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/TaggerFactory.java index 639b1011fc..7b7440108e 100644 --- a/grobid-core/src/main/java/org/grobid/core/engines/tagging/TaggerFactory.java +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/TaggerFactory.java @@ -14,7 +14,7 @@ /** * Factory for a sequence labelling, aka a tagger, instance. - * Supported implementations are CRF (CRFPP, Wapiti) and Deep Learning (DeLFT) + * Supported implementations are CRF (CRFPP, Wapiti) and Deep Learning (DeLFT) * */ public class TaggerFactory { @@ -22,7 +22,8 @@ public class TaggerFactory { private static Map<GrobidModel, GenericTagger> cache = new HashMap<>(); - private TaggerFactory() {} + private TaggerFactory() { + } public static synchronized GenericTagger getTagger(GrobidModel model) { return getTagger(model, GrobidProperties.getGrobidEngine(model), GrobidProperties.getDelftArchitecture(model)); @@ -35,11 +36,11 @@ public static synchronized GenericTagger getTagger(GrobidModel model, GrobidCRFE public static synchronized GenericTagger getTagger(GrobidModel model, GrobidCRFEngine engine, String architecture) { GenericTagger t = cache.get(model); if (t == null) { - if(model.equals(GrobidModels.DUMMY)) { + if (model.equals(GrobidModels.DUMMY)) { return new DummyTagger(model); } - if(engine != null) { + if (engine != null) { switch (engine) { case CRFPP: t = new CRFPPTagger(model); @@ -50,12 +51,17 @@ public static synchronized GenericTagger getTagger(GrobidModel model, GrobidCRFE case DELFT: t = new DeLFTTagger(model, architecture); break; + case ONNX: + t = new OnnxTagger(model, GrobidProperties.getOnnxArchitecture(model)); + break; default: - throw new IllegalStateException("Unsupported Grobid sequence labelling engine: " + engine.getExt()); + throw new IllegalStateException( + "Unsupported Grobid sequence labelling engine: " + engine.getExt()); } cache.put(model, t); } else { - throw new IllegalStateException("Unsupported or null Grobid sequence labelling engine: " + engine.getExt()); + throw new IllegalStateException( + "Unsupported or null Grobid sequence labelling engine: " + engine.getExt()); } } return t; diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/CRFDecoder.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/CRFDecoder.java new file mode 100644 index 0000000000..02d95e29b7 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/CRFDecoder.java @@ -0,0 +1,186 @@ +package org.grobid.core.engines.tagging.delft; + +import com.google.gson.Gson; +import com.google.gson.JsonObject; + +import java.io.FileReader; +import java.io.IOException; +import java.nio.file.Path; +import java.util.Arrays; + +/** + * CRF Viterbi decoder for use with ONNX-exported DeLFT models. + * + * Performs Viterbi decoding given emission scores and learned transition + * matrices. + * The transition matrices are loaded from JSON exported by Python. + */ +public class CRFDecoder { + + private final int numTags; + private final float[][] transitions; // [from_tag][to_tag] + private final float[] startTransitions; // [num_tags] + private final float[] endTransitions; // [num_tags] + + /** + * Create a CRF decoder with learned parameters. + * + * @param transitions Transition matrix [from_tag][to_tag] + * @param startTransitions Start transition scores + * @param endTransitions End transition scores + */ + public CRFDecoder(float[][] transitions, float[] startTransitions, float[] endTransitions) { + this.numTags = transitions.length; + this.transitions = transitions; + this.startTransitions = startTransitions; + this.endTransitions = endTransitions; + } + + /** + * Load CRF parameters from JSON file exported by Python. + * + * @param jsonPath Path to crf_params.json + * @return CRFDecoder instance + */ + public static CRFDecoder fromJson(Path jsonPath) throws IOException { + Gson gson = new Gson(); + try (FileReader reader = new FileReader(jsonPath.toFile())) { + JsonObject json = gson.fromJson(reader, JsonObject.class); + + // Parse transitions [num_tags][num_tags] + double[][] transitionsDouble = gson.fromJson(json.get("transitions"), double[][].class); + float[][] transitions = toFloatArray2D(transitionsDouble); + + // Parse start transitions [num_tags] + double[] startDouble = gson.fromJson(json.get("startTransitions"), double[].class); + float[] startTransitions = toFloatArray(startDouble); + + // Parse end transitions [num_tags] + double[] endDouble = gson.fromJson(json.get("endTransitions"), double[].class); + float[] endTransitions = toFloatArray(endDouble); + + return new CRFDecoder(transitions, startTransitions, endTransitions); + } + } + + private static float[] toFloatArray(double[] doubles) { + float[] floats = new float[doubles.length]; + for (int i = 0; i < doubles.length; i++) { + floats[i] = (float) doubles[i]; + } + return floats; + } + + private static float[][] toFloatArray2D(double[][] doubles) { + float[][] floats = new float[doubles.length][]; + for (int i = 0; i < doubles.length; i++) { + floats[i] = toFloatArray(doubles[i]); + } + return floats; + } + + /** + * Decode the best tag sequence using Viterbi algorithm. + * + * @param emissions Emission scores from the model [seq_len][num_tags] + * @param mask Mask indicating valid tokens (true = valid). Can be null. + * @return Best tag sequence as array of tag indices + */ + public int[] decode(float[][] emissions, boolean[] mask) { + int seqLength = emissions.length; + + if (mask == null) { + mask = new boolean[seqLength]; + Arrays.fill(mask, true); + } + + // Find actual sequence length (excluding padding) + int actualLength = 0; + for (int i = 0; i < seqLength; i++) { + if (mask[i]) + actualLength = i + 1; + } + + if (actualLength == 0) { + return new int[0]; + } + + // Viterbi score matrix [seq_len][num_tags] + float[][] viterbiScore = new float[actualLength][numTags]; + + // Backpointer matrix [seq_len][num_tags] + int[][] backpointers = new int[actualLength][numTags]; + + // Initialize first position with start transitions + emissions + for (int tag = 0; tag < numTags; tag++) { + viterbiScore[0][tag] = startTransitions[tag] + emissions[0][tag]; + } + + // Forward pass + for (int t = 1; t < actualLength; t++) { + for (int currentTag = 0; currentTag < numTags; currentTag++) { + float bestScore = Float.NEGATIVE_INFINITY; + int bestPrevTag = 0; + + for (int prevTag = 0; prevTag < numTags; prevTag++) { + float score = viterbiScore[t - 1][prevTag] + + transitions[prevTag][currentTag] + + emissions[t][currentTag]; + + if (score > bestScore) { + bestScore = score; + bestPrevTag = prevTag; + } + } + + viterbiScore[t][currentTag] = bestScore; + backpointers[t][currentTag] = bestPrevTag; + } + } + + // Add end transitions to find best final tag + float bestFinalScore = Float.NEGATIVE_INFINITY; + int bestLastTag = 0; + + for (int tag = 0; tag < numTags; tag++) { + float score = viterbiScore[actualLength - 1][tag] + endTransitions[tag]; + if (score > bestFinalScore) { + bestFinalScore = score; + bestLastTag = tag; + } + } + + // Backtrack to find best sequence + int[] bestPath = new int[actualLength]; + bestPath[actualLength - 1] = bestLastTag; + + for (int t = actualLength - 2; t >= 0; t--) { + bestPath[t] = backpointers[t + 1][bestPath[t + 1]]; + } + + return bestPath; + } + + /** + * Decode multiple sequences (batch processing). + * + * @param emissions Batch of emission scores [batch_size][seq_len][num_tags] + * @param masks Masks for each sequence. Can be null. + * @return Array of best tag sequences + */ + public int[][] decodeBatch(float[][][] emissions, boolean[][] masks) { + int batchSize = emissions.length; + int[][] results = new int[batchSize][]; + + for (int i = 0; i < batchSize; i++) { + boolean[] mask = (masks != null) ? masks[i] : null; + results[i] = decode(emissions[i], mask); + } + + return results; + } + + public int getNumTags() { + return numTags; + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationModel.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationModel.java new file mode 100644 index 0000000000..aad802fec9 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationModel.java @@ -0,0 +1,235 @@ +package org.grobid.core.engines.tagging.delft; + +import ai.onnxruntime.OrtException; +import com.google.gson.Gson; +import com.google.gson.JsonArray; +import com.google.gson.JsonObject; +import org.grobid.core.analyzers.GrobidAnalyzer; +import org.grobid.core.engines.tagging.GenericClassifier; +import org.grobid.core.layout.LayoutToken; +import org.grobid.core.utilities.GrobidProperties; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.FileReader; +import java.io.IOException; +import java.nio.file.Path; +import java.time.LocalDateTime; +import java.time.format.DateTimeFormatter; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; + +/** + * ONNX-based text classification model. + * + * Provides pure Java inference for classification models exported from DeLFT, + * eliminating the need for JEP/Python at runtime. + * + * Model directory structure: + * - classifier.onnx : The ONNX model + * - config.json : Model config (maxlen, wordEmbeddingSize, embeddingsName) + * - labels.json : Label mappings (labels array, indexToLabel) + */ +public class OnnxClassificationModel implements GenericClassifier { + + private static final Logger LOGGER = LoggerFactory.getLogger(OnnxClassificationModel.class); + + private final OnnxClassificationRunner modelRunner; + private final WordEmbeddings embeddings; + private final String[] labels; + private final Map<String, Integer> labelToIndex; + private final int maxlen; + private final int embeddingSize; + private final String modelName; + + /** + * Load an ONNX classification model from a directory. + * + * @param modelDir Directory containing classifier.onnx, config.json, + * labels.json + */ + public OnnxClassificationModel(Path modelDir) throws IOException, OrtException { + Gson gson = new Gson(); + + // Read config.json + Path configPath = modelDir.resolve("config.json"); + JsonObject config; + try (FileReader reader = new FileReader(configPath.toFile())) { + config = gson.fromJson(reader, JsonObject.class); + } + + this.modelName = config.get("modelName").getAsString(); + this.maxlen = config.get("maxlen").getAsInt(); + this.embeddingSize = config.get("wordEmbeddingSize").getAsInt(); + String embeddingsName = config.get("embeddingsName").getAsString(); + + // Read labels.json + Path labelsPath = modelDir.resolve("labels.json"); + JsonObject labelsJson; + try (FileReader reader = new FileReader(labelsPath.toFile())) { + labelsJson = gson.fromJson(reader, JsonObject.class); + } + + JsonArray labelsArray = labelsJson.getAsJsonArray("labels"); + this.labels = new String[labelsArray.size()]; + for (int i = 0; i < labelsArray.size(); i++) { + this.labels[i] = labelsArray.get(i).getAsString(); + } + + JsonObject labelToIndexJson = labelsJson.getAsJsonObject("labelToIndex"); + this.labelToIndex = new HashMap<>(); + for (String label : labelToIndexJson.keySet()) { + this.labelToIndex.put(label, labelToIndexJson.get(label).getAsInt()); + } + + // Load embeddings from DeLFT path + String delftPath = GrobidProperties.getDeLFTFilePath(); + Path embeddingsPath = Path.of(delftPath, "data", "db", embeddingsName); + + LOGGER.info("Loading ONNX classification model from: {}", modelDir); + LOGGER.info("Loading embeddings from: {}", embeddingsPath); + + // Load ONNX model via runner + this.modelRunner = new OnnxClassificationRunner(modelDir.resolve("classifier.onnx")); + + // Load embeddings + this.embeddings = WordEmbeddings.getInstance(embeddingsPath, embeddingSize); + + LOGGER.info("ONNX classification model {} loaded", modelName); + LOGGER.info("Labels: {}", String.join(", ", labels)); + } + + /** + * Classify texts and return results in DeLFT JSON format. + * + * @param texts List of texts to classify + * @return JSON string matching DeLFT classifier output format + */ + @Override + public String classify(List<String> texts) throws Exception { + if (texts == null || texts.isEmpty()) { + return null; + } + + int batchSize = texts.size(); + float[][][] batchEmbeddings = new float[batchSize][maxlen][embeddingSize]; + + // Process each text + for (int b = 0; b < batchSize; b++) { + String text = texts.get(b); + + // Tokenize using GrobidAnalyzer (same as sequence labeling) + List<LayoutToken> tokens = GrobidAnalyzer.getInstance().tokenizeWithLayoutToken(text); + List<String> words = new ArrayList<>(); + for (LayoutToken token : tokens) { + String txt = token.getText(); + if (txt != null && !txt.trim().isEmpty()) { + words.add(txt); + } + } + + // Get embeddings for words + String[] wordArray = words.toArray(new String[0]); + float[][] wordEmbs = embeddings.getEmbeddings(wordArray); + + // Copy to batch (pad/truncate to maxlen) + int numTokens = Math.min(wordEmbs.length, maxlen); + for (int i = 0; i < numTokens; i++) { + batchEmbeddings[b][i] = wordEmbs[i]; + } + // Rest is zero-padded (default float array initialization) + } + + // Run inference + float[][] predictions = runInference(batchEmbeddings); + + // Format as DeLFT JSON + return formatAsJson(texts, predictions); + } + + /** + * Run ONNX inference. + * + * @param embeddingsInput Input embeddings [batch, maxlen, embeddingSize] + * @return Predictions [batch, numClasses] (softmax-normalized probabilities) + */ + private float[][] runInference(float[][][] embeddingsInput) throws OrtException { + // Delegate to runner for ONNX inference + float[][] logits = modelRunner.runInference(embeddingsInput); + + // Apply softmax to convert logits to probabilities + int batchSize = logits.length; + int numClasses = logits[0].length; + float[][] predictions = new float[batchSize][numClasses]; + for (int b = 0; b < batchSize; b++) { + predictions[b] = softmax(logits[b]); + } + + return predictions; + } + + /** + * Apply softmax activation to convert logits to probabilities. + * For single-label classification (copyright, license). + */ + private float[] softmax(float[] logits) { + float max = Float.NEGATIVE_INFINITY; + for (float v : logits) { + if (v > max) + max = v; + } + + float sum = 0.0f; + float[] exp = new float[logits.length]; + for (int i = 0; i < logits.length; i++) { + exp[i] = (float) Math.exp(logits[i] - max); // subtract max for numerical stability + sum += exp[i]; + } + + float[] probs = new float[logits.length]; + for (int i = 0; i < logits.length; i++) { + probs[i] = exp[i] / sum; + } + return probs; + } + + /** + * Format predictions as DeLFT-compatible JSON. + */ + private String formatAsJson(List<String> texts, float[][] predictions) { + JsonObject root = new JsonObject(); + + JsonArray classifications = new JsonArray(); + for (int i = 0; i < texts.size(); i++) { + JsonObject classificationEntry = new JsonObject(); + classificationEntry.addProperty("text", texts.get(i)); + + // Add probability for each label + for (int j = 0; j < labels.length; j++) { + classificationEntry.addProperty(labels[j], predictions[i][j]); + } + + classifications.add(classificationEntry); + } + + root.add("classifications", classifications); + root.addProperty("model", modelName); + root.addProperty("software", "DeLFT"); + root.addProperty("date", LocalDateTime.now().format(DateTimeFormatter.ISO_LOCAL_DATE_TIME)); + + Gson gson = new Gson(); + return gson.toJson(root); + } + + @Override + public void close() throws IOException { + if (modelRunner != null) { + modelRunner.close(); + } + if (embeddings != null) { + embeddings.close(); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationRunner.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationRunner.java new file mode 100644 index 0000000000..38f7f05393 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxClassificationRunner.java @@ -0,0 +1,137 @@ +package org.grobid.core.engines.tagging.delft; + +import ai.onnxruntime.*; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.Closeable; +import java.nio.FloatBuffer; +import java.nio.file.Path; +import java.util.HashMap; +import java.util.Map; + +/** + * ONNX Runtime wrapper for running DeLFT classification models. + * + * Handles low-level ONNX operations: loading models, creating tensors, + * running inference, and managing resources. The higher-level + * OnnxClassificationModel handles embeddings, tokenization, and output + * formatting. + */ +public class OnnxClassificationRunner implements Closeable { + + private static final Logger LOGGER = LoggerFactory.getLogger(OnnxClassificationRunner.class); + + private final OrtEnvironment env; + private final OrtSession session; + private final String inputName; + + /** + * Load an ONNX classification model. + * + * @param modelPath Path to the .onnx file + */ + public OnnxClassificationRunner(Path modelPath) throws OrtException { + this.env = OrtEnvironment.getEnvironment(); + + OrtSession.SessionOptions options = new OrtSession.SessionOptions(); + options.setOptimizationLevel(OrtSession.SessionOptions.OptLevel.ALL_OPT); + + // Configure threading for optimal CPU inference performance + // Since GROBID manages concurrency at the worker level (e.g., 10 concurrent + // workers), use single-threaded inference per session to avoid CPU + // oversubscription + options.setIntraOpNumThreads(1); + + // interOpNumThreads: threads for parallel execution of multiple operators + // Set to 1 since GROBID manages concurrency at a higher level + options.setInterOpNumThreads(1); + + // Use sequential execution mode (vs parallel) since GROBID handles parallelism + options.setExecutionMode(OrtSession.SessionOptions.ExecutionMode.SEQUENTIAL); + + this.session = env.createSession(modelPath.toString(), options); + + // Get the first input name (classification models typically have one input) + this.inputName = session.getInputNames().iterator().next(); + + LOGGER.info("Loaded ONNX classification model from {} (single-threaded, sequential mode)", modelPath); + LOGGER.info("Input names: {}", session.getInputNames()); + LOGGER.info("Output names: {}", session.getOutputNames()); + } + + /** + * Run inference on embeddings input. + * + * @param embeddings Input embeddings [batch, maxlen, embeddingSize] + * @return Raw logits [batch, numClasses] (not yet softmax-normalized) + */ + public float[][] runInference(float[][][] embeddings) throws OrtException { + int batchSize = embeddings.length; + int maxlen = embeddings[0].length; + int embeddingSize = embeddings[0][0].length; + + // Flatten embeddings for ONNX tensor + float[] flat = flatten3D(embeddings); + + // Create input tensor + OnnxTensor inputTensor = OnnxTensor.createTensor(env, + FloatBuffer.wrap(flat), + new long[] { batchSize, maxlen, embeddingSize }); + + Map<String, OnnxTensor> inputs = new HashMap<>(); + inputs.put(inputName, inputTensor); + + try (OrtSession.Result result = session.run(inputs)) { + // Get output - should be [batch, numClasses] (raw logits) + OnnxTensor outputTensor = (OnnxTensor) result.get(0); + long[] shape = outputTensor.getInfo().getShape(); + int numClasses = (int) shape[1]; + + float[] outputFlat = outputTensor.getFloatBuffer().array(); + + // Reshape to 2D + float[][] logits = new float[batchSize][numClasses]; + int idx = 0; + for (int b = 0; b < batchSize; b++) { + for (int c = 0; c < numClasses; c++) { + logits[b][c] = outputFlat[idx++]; + } + } + + return logits; + } finally { + inputTensor.close(); + } + } + + /** + * Flatten 3D array to 1D for ONNX tensor creation. + */ + private float[] flatten3D(float[][][] arr) { + int d1 = arr.length; + int d2 = arr[0].length; + int d3 = arr[0][0].length; + float[] flat = new float[d1 * d2 * d3]; + int idx = 0; + for (int i = 0; i < d1; i++) { + for (int j = 0; j < d2; j++) { + for (int k = 0; k < d3; k++) { + flat[idx++] = arr[i][j][k]; + } + } + } + return flat; + } + + @Override + public void close() { + try { + if (session != null) { + session.close(); + } + } catch (Exception e) { + LOGGER.warn("Error closing ONNX session", e); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModel.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModel.java new file mode 100644 index 0000000000..7db6e1ea51 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModel.java @@ -0,0 +1,767 @@ +package org.grobid.core.engines.tagging.delft; + +import ai.onnxruntime.OrtException; +import com.google.gson.Gson; +import com.google.gson.JsonObject; +import org.grobid.core.layout.LayoutToken; +import org.grobid.core.engines.label.TaggingLabels; +import org.grobid.core.utilities.GrobidProperties; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.Closeable; +import java.io.FileReader; +import java.io.IOException; +import java.nio.file.Path; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; + +/** + * ONNX Runtime wrapper for running DeLFT encoder models. + */ +public class OnnxSequenceLabellingModel implements Closeable { + + private static final Logger LOGGER = LoggerFactory.getLogger(OnnxSequenceLabellingModel.class); + + private final OnnxSequenceLabellingRunner modelRunner; + private final CRFDecoder crfDecoder; + private final Preprocessor preprocessor; + private final WordEmbeddings embeddings; + private final int maxSeqLength; + + public OnnxSequenceLabellingModel(Path modelDir) throws IOException, OrtException { + // Read config.json + Gson gson = new Gson(); + Path configPath = modelDir.resolve("config.json"); + JsonObject config; + try (FileReader reader = new FileReader(configPath.toFile())) { + config = gson.fromJson(reader, JsonObject.class); + } + + int embeddingSize = config.get("wordEmbeddingSize").getAsInt(); + this.maxSeqLength = config.get("maxSequenceLength").getAsInt(); + String embeddingsName = config.get("embeddingsName").getAsString(); + + // Embeddings are stored under delft installation path: + // {delft}/data/db/{name} + String delftPath = GrobidProperties.getDeLFTFilePath(); + Path embeddingsPath = Path.of(delftPath, "data", "db", embeddingsName); + + LOGGER.info("Loading ONNX model from: {}", modelDir); + LOGGER.info("Loading embeddings from: {}", embeddingsPath); + + // Load components + this.modelRunner = new OnnxSequenceLabellingRunner(modelDir.resolve("encoder.onnx")); + this.crfDecoder = CRFDecoder.fromJson(modelDir.resolve("crf_params.json")); + this.preprocessor = Preprocessor.fromJson(modelDir.resolve("vocab.json")); + this.embeddings = WordEmbeddings.getInstance(embeddingsPath, embeddingSize); + + LOGGER.info("DeLFT model loaded from {}", modelDir); + LOGGER.info("Model has features: {}", preprocessor.hasFeatures()); + } + + /** + * Load a DeLFT model from exported directory. + * + * @param modelDir Directory containing encoder.onnx, crf_params.json, + * vocab.json + * @param embeddingsPath Path to LMDB embeddings database + * @param embeddingSize Dimension of word embeddings + * @param maxSeqLength Maximum sequence length + */ + public OnnxSequenceLabellingModel(Path modelDir, Path embeddingsPath, int embeddingSize, int maxSeqLength) + throws IOException, OrtException { + + this.maxSeqLength = maxSeqLength; + + // Load components + this.modelRunner = new OnnxSequenceLabellingRunner(modelDir.resolve("encoder.onnx")); + this.crfDecoder = CRFDecoder.fromJson(modelDir.resolve("crf_params.json")); + this.preprocessor = Preprocessor.fromJson(modelDir.resolve("vocab.json")); + this.embeddings = WordEmbeddings.getInstance(embeddingsPath, embeddingSize); + + LOGGER.info("DeLFT model loaded from {}", modelDir); + LOGGER.info("Model has features: {}", preprocessor.hasFeatures()); + } + + /** + * Annotate text with sequence labels (no features). + * + * @param text Input text + * @return Annotation result + */ + public AnnotationResult annotate(String text) throws OrtException { + List<LayoutToken> tokens = preprocessor.tokenize(text); + String[] words = new String[tokens.size()]; + for (int i = 0; i < tokens.size(); i++) { + words[i] = tokens.get(i).getText(); + } + + return annotateTokens(words, null); + } + + /** + * Annotate tokens with features. + * + * For BidLSTM_CRF_FEATURES models, features must be provided. + * Each row in features corresponds to a token, with one value per feature + * column. + * + * @param tokens Array of token strings + * @param features Feature values per token [numTokens][numFeatures], can be + * null for non-feature models + * @return Annotation result + */ + public AnnotationResult annotateTokens(String[] tokens, String[][] features) throws OrtException { + int numTokens = Math.min(tokens.length, maxSeqLength); + if (tokens.length > maxSeqLength) { + LOGGER.warn("Input sequence length {} exceeds maxSeqLength {}. Truncating.", tokens.length, maxSeqLength); + } + + if (numTokens == 0) { + return new AnnotationResult(null, new String[0], new String[0]); + } + + // Truncate to max sequence length + String[] words = new String[numTokens]; + System.arraycopy(tokens, 0, words, 0, numTokens); + + // Get embeddings [seq_len][embed_size] + float[][] wordEmbs = embeddings.getEmbeddings(words); + + // Pad to maxSeqLength + float[][] paddedEmbs = new float[maxSeqLength][embeddings.getEmbeddingSize()]; + for (int i = 0; i < numTokens; i++) { + paddedEmbs[i] = wordEmbs[i]; + } + + // Get char indices [seq_len][max_char] + List<LayoutToken> layoutTokens = new ArrayList<>(); + for (String word : words) { + LayoutToken lt = new LayoutToken(); + lt.setText(word); + layoutTokens.add(lt); + } + long[][] charIndices = preprocessor.tokensToCharIndices(layoutTokens, maxSeqLength); + + // Create batch of 1 + float[][][] batchEmbs = new float[][][] { paddedEmbs }; + long[][][] batchChars = new long[][][] { charIndices }; + + // Handle features + long[][][] batchFeatures = null; + if (preprocessor.hasFeatures() && features != null) { + long[][] featureIndices = preprocessor.tokensToFeatureIndices(features, maxSeqLength); + batchFeatures = new long[][][] { featureIndices }; + } + + // Run model + float[][][] emissions = modelRunner.runInference(batchEmbs, batchChars, batchFeatures); + + // CRF decode + boolean[] mask = preprocessor.createMask(numTokens, maxSeqLength); + int[] tagIndices = crfDecoder.decode(emissions[0], mask); + + // Convert to tag names (only for actual tokens) + String[] tags = new String[numTokens]; + for (int i = 0; i < numTokens; i++) { + tags[i] = delft2grobidLabel( + preprocessor.getTagIndex().getOrDefault(tagIndices[i], TaggingLabels.IOB_OTHER_LABEL)); + } + + return new AnnotationResult(String.join(" ", words), words, tags); + } + + /** + * Annotate multiple token sequences in a single batch inference call. + * All sequences are padded to maxSeqLength. + * + * @param tokensBatch Array of token arrays [batchSize][numTokens] + * @param featuresBatch Feature values per token + * [batchSize][numTokens][numFeatures], can be null + * @return Array of AnnotationResult, one per input sequence + */ + public AnnotationResult[] annotateTokensBatch(String[][] tokensBatch, String[][][] featuresBatch) + throws OrtException { + int batchSize = tokensBatch.length; + + if (batchSize == 0) { + return new AnnotationResult[0]; + } + + // Prepare arrays to store actual token counts for each sequence + int[] numTokensPerSeq = new int[batchSize]; + + // Prepare batch data + float[][][] batchEmbs = new float[batchSize][maxSeqLength][embeddings.getEmbeddingSize()]; + long[][][] batchChars = new long[batchSize][maxSeqLength][]; + long[][][] batchFeatures = null; + + if (preprocessor.hasFeatures() && featuresBatch != null) { + batchFeatures = new long[batchSize][][]; + } + + for (int b = 0; b < batchSize; b++) { + String[] tokens = tokensBatch[b]; + int numTokens = Math.min(tokens.length, maxSeqLength); + if (tokens.length > maxSeqLength) { + LOGGER.warn("Input sequence length {} exceeds maxSeqLength {}. Truncating.", tokens.length, + maxSeqLength); + } + numTokensPerSeq[b] = numTokens; + + if (numTokens == 0) { + // Initialize with zeros for empty sequences + for (int i = 0; i < maxSeqLength; i++) { + batchEmbs[b][i] = new float[embeddings.getEmbeddingSize()]; + batchChars[b][i] = new long[preprocessor.getMaxCharLength()]; + } + if (batchFeatures != null) { + batchFeatures[b] = new long[maxSeqLength][preprocessor.getNumFeatures()]; + } + continue; + } + + // Truncate to max sequence length + String[] words = new String[numTokens]; + System.arraycopy(tokens, 0, words, 0, numTokens); + + // Get embeddings and pad + float[][] wordEmbs = embeddings.getEmbeddings(words); + for (int i = 0; i < numTokens; i++) { + batchEmbs[b][i] = wordEmbs[i]; + } + for (int i = numTokens; i < maxSeqLength; i++) { + batchEmbs[b][i] = new float[embeddings.getEmbeddingSize()]; + } + + // Get char indices + List<LayoutToken> layoutTokens = new ArrayList<>(); + for (String word : words) { + LayoutToken lt = new LayoutToken(); + lt.setText(word); + layoutTokens.add(lt); + } + batchChars[b] = preprocessor.tokensToCharIndices(layoutTokens, maxSeqLength); + + // Handle features + if (batchFeatures != null) { + if (featuresBatch != null && featuresBatch[b] != null) { + batchFeatures[b] = preprocessor.tokensToFeatureIndices(featuresBatch[b], maxSeqLength); + } else { + batchFeatures[b] = new long[maxSeqLength][preprocessor.getNumFeatures()]; + } + } + } + + // Run batch inference + float[][][] emissions = modelRunner.runInference(batchEmbs, batchChars, batchFeatures); + + // Decode each sequence + AnnotationResult[] results = new AnnotationResult[batchSize]; + for (int b = 0; b < batchSize; b++) { + int numTokens = numTokensPerSeq[b]; + + if (numTokens == 0) { + results[b] = new AnnotationResult(null, new String[0], new String[0]); + continue; + } + + // CRF decode + boolean[] mask = preprocessor.createMask(numTokens, maxSeqLength); + int[] tagIndices = crfDecoder.decode(emissions[b], mask); + + // Convert to tag names (only for actual tokens) + String[] tags = new String[numTokens]; + String[] words = new String[numTokens]; + System.arraycopy(tokensBatch[b], 0, words, 0, numTokens); + + for (int i = 0; i < numTokens; i++) { + tags[i] = delft2grobidLabel( + preprocessor.getTagIndex().getOrDefault(tagIndices[i], TaggingLabels.IOB_OTHER_LABEL)); + } + + results[b] = new AnnotationResult(String.join(" ", words), words, tags); + } + + return results; + } + + /** + * Check if this model requires features. + */ + public boolean hasFeatures() { + return preprocessor.hasFeatures(); + } + + /** + * Get the number of features expected per token (0 if no features). + */ + public int getNumFeatures() { + return preprocessor.getNumFeatures(); + } + + /** + * Maximum sequence length supported by the model. + * <p> + * For the DeLFT-exported ONNX bundles shipped with GROBID, this value is read + * from the accompanying {@code config.json} (field {@code maxSequenceLength}). + */ + public int getMaxSeqLength() { + return maxSeqLength; + } + + /** + * Read the maximum sequence length from a DeLFT ONNX bundle directory. + * <p> + * This method only parses {@code config.json} and does not load ONNX Runtime, + * embeddings (LMDB) or any other native dependency. + * + * @param modelDir directory containing {@code config.json} + * @return maxSequenceLength from config.json + */ + public static int readMaxSequenceLength(Path modelDir) throws IOException { + Gson gson = new Gson(); + Path configPath = modelDir.resolve("config.json"); + try (FileReader reader = new FileReader(configPath.toFile())) { + JsonObject config = gson.fromJson(reader, JsonObject.class); + return config.get("maxSequenceLength").getAsInt(); + } + } + + /** + * Annotate multiple texts in batch. + */ + public List<AnnotationResult> annotateBatch(List<String> texts) throws OrtException { + List<AnnotationResult> results = new ArrayList<>(); + for (String text : texts) { + results.add(annotate(text)); + } + return results; + } + + /** + * Label GROBID-formatted input data with support for long sequences. + * + * For sequences exceeding maxSeqLength, this method chunks the sequence, + * runs inference on each chunk independently, and concatenates the results. + * This matches the behavior of DeLFT's Python grobidTagger.tag() method. + * + * Input format: token\tfeature1\tfeature2\t...\n + * Output format: token\tfeature1\tfeature2\t...\tlabel\n + * + * @param data GROBID feature data + * @return Labeled output in GROBID format + */ + public String labelGrobidInput(String data) { + try { + // Parse input into sequences (separated by empty lines) + List<List<String>> sequences = new ArrayList<>(); + List<String> currentSequence = new ArrayList<>(); + + String[] lines = data.split("\n", -1); // -1 to keep trailing empty strings + + for (String line : lines) { + if (line.trim().isEmpty()) { + if (!currentSequence.isEmpty()) { + sequences.add(currentSequence); + currentSequence = new ArrayList<>(); + } + } else { + currentSequence.add(line); + } + } + // Don't forget the last sequence if it doesn't end with empty line + if (!currentSequence.isEmpty()) { + sequences.add(currentSequence); + } + + if (sequences.isEmpty()) { + return ""; + } + + // Process each sequence independently (with chunking if needed) + List<List<String>> allSequenceLabels = new ArrayList<>(); + + for (List<String> sequence : sequences) { + List<String> sequenceLabels = labelSequenceWithChunking(sequence); + allSequenceLabels.add(sequenceLabels); + } + + // Rebuild output with original structure + StringBuilder output = new StringBuilder(); + int seqIdx = 0; + int tokenInSeqIdx = 0; + boolean inSequence = false; + + for (String line : lines) { + if (line.trim().isEmpty()) { + if (inSequence && seqIdx < sequences.size()) { + // End of a sequence - add separator + output.append("\n"); + seqIdx++; + tokenInSeqIdx = 0; + inSequence = false; + } + } else { + inSequence = true; + if (seqIdx < allSequenceLabels.size() && + tokenInSeqIdx < allSequenceLabels.get(seqIdx).size()) { + String label = allSequenceLabels.get(seqIdx).get(tokenInSeqIdx); + output.append(line).append("\t").append(label).append("\n"); + tokenInSeqIdx++; + } + } + } + + return output.toString(); + } catch (OrtException e) { + throw new RuntimeException("ONNX inference failed", e); + } + } + + /** + * Label a single sequence, chunking if it exceeds maxSeqLength. + * + * @param sequenceLines Lines of the sequence (token\tfeatures format) + * @return List of labels, one per token + */ + private List<String> labelSequenceWithChunking(List<String> sequenceLines) throws OrtException { + // Parse tokens and features from the sequence + List<String[]> tokensWithFeatures = new ArrayList<>(); + for (String line : sequenceLines) { + String[] parts = line.split("[\\t\\s]+"); + tokensWithFeatures.add(parts); + } + + int totalTokens = tokensWithFeatures.size(); + + // If sequence fits in one chunk, process directly + if (totalTokens <= maxSeqLength) { + return labelTokensWithFeatures(tokensWithFeatures); + } + + // Collect all chunks for batch processing + List<List<String[]>> chunks = new ArrayList<>(); + int offset = 0; + + while (offset < totalTokens) { + int chunkEnd = Math.min(offset + maxSeqLength, totalTokens); + chunks.add(new ArrayList<>(tokensWithFeatures.subList(offset, chunkEnd))); + offset = chunkEnd; + } + + // Convert chunks to batch arrays + int batchSize = chunks.size(); + String[][] tokensBatch = new String[batchSize][]; + String[][][] featuresBatch = new String[batchSize][][]; + + List<Integer> featuresIndices = preprocessor.getFeaturesIndices(); + + for (int i = 0; i < batchSize; i++) { + List<String[]> chunk = chunks.get(i); + tokensBatch[i] = new String[chunk.size()]; + featuresBatch[i] = null; + + for (int j = 0; j < chunk.size(); j++) { + String[] parts = chunk.get(j); + tokensBatch[i][j] = parts[0]; + + if (featuresIndices != null && !featuresIndices.isEmpty()) { + if (featuresBatch[i] == null) { + featuresBatch[i] = new String[chunk.size()][featuresIndices.size()]; + } + + // We need to map the features from the input line to the features expected by + // the model + // The input line parts[0] is the token, parts[1]... are features + // featuresIndices contains the 0-based index of the feature in the training + // data + // We assume the input data has the same structure as training data (Grobid + // structure) + + for (int k = 0; k < featuresIndices.size(); k++) { + int featureIndex = featuresIndices.get(k); + // IMPORTANT: featuresIndices values (e.g., 9, 10, ...) are 1-based indices + // into Python's features array, which excludes the token. + // In Python: features = pieces[1:], so features[9] = pieces[10]. + // In Java: parts[0] is token, so we need parts[featureIndex + 1] to match. + int adjustedIndex = featureIndex + 1; + + if (adjustedIndex < parts.length) { + featuresBatch[i][j][k] = parts[adjustedIndex]; + } else { + // Missing feature in input + featuresBatch[i][j][k] = "0"; + } + } + } + } + } + + // Run batch inference + AnnotationResult[] results = annotateTokensBatch(tokensBatch, featuresBatch); + + // Combine results + List<String> allLabels = new ArrayList<>(); + for (AnnotationResult result : results) { + allLabels.addAll(Arrays.asList(result.getLabels())); + } + + return allLabels; + } + + /** + * Label a list of tokens with features. + * + * @param tokensWithFeatures Each element is [token, feature1, feature2, ...] + * @return List of labels + */ + private List<String> labelTokensWithFeatures(List<String[]> tokensWithFeatures) throws OrtException { + if (tokensWithFeatures.isEmpty()) { + return new ArrayList<>(); + } + + // Extract tokens and selected features (using featuresIndices) + String[] tokens = new String[tokensWithFeatures.size()]; + String[][] features = null; + List<Integer> featuresIndices = preprocessor.getFeaturesIndices(); + + for (int i = 0; i < tokensWithFeatures.size(); i++) { + String[] parts = tokensWithFeatures.get(i); + tokens[i] = parts[0]; + + // Extract only the features specified in featuresIndices + if (featuresIndices != null && !featuresIndices.isEmpty()) { + if (features == null) { + features = new String[tokensWithFeatures.size()][featuresIndices.size()]; + } + for (int k = 0; k < featuresIndices.size(); k++) { + int featureIndex = featuresIndices.get(k); + // IMPORTANT: featuresIndices values (e.g., 9, 10, ...) are 1-based indices + // into Python's features array, which excludes the token. + // In Python: features = pieces[1:], so features[9] = pieces[10]. + // In Java: parts[0] is token, so we need parts[featureIndex + 1] to match. + int adjustedIndex = featureIndex + 1; + if (adjustedIndex < parts.length) { + features[i][k] = parts[adjustedIndex]; + } else { + features[i][k] = "0"; + } + } + } + } + + // Run annotation + AnnotationResult result = annotateTokens(tokens, features); + return Arrays.asList(result.getLabels()); + } + + @Override + public void close() { + if (modelRunner != null) + modelRunner.close(); + if (embeddings != null) + embeddings.close(); + } + + private static String delft2grobidLabel(String label) { + if (label.equals(TaggingLabels.IOB_OTHER_LABEL) || label.trim().equals("<PAD>")) { + return TaggingLabels.OTHER_LABEL; + } else if (label.startsWith(TaggingLabels.IOB_START_ENTITY_LABEL_PREFIX)) { + return label.replace(TaggingLabels.IOB_START_ENTITY_LABEL_PREFIX, + TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX); + } else if (label.startsWith(TaggingLabels.IOB_INSIDE_LABEL_PREFIX)) { + return label.replace(TaggingLabels.IOB_INSIDE_LABEL_PREFIX, + TaggingLabels.GROBID_INSIDE_ENTITY_LABEL_PREFIX); + } + return label; + } + + /** + * Annotation result containing tokens and labels. + */ + public static class AnnotationResult { + private final String text; + private final String[] tokens; + private final String[] labels; + + public AnnotationResult(String text, String[] tokens, String[] labels) { + this.text = text; + this.tokens = tokens; + this.labels = labels; + } + + public String getText() { + return text; + } + + public String[] getTokens() { + return tokens; + } + + public String[] getLabels() { + return labels; + } + + /** + * Represents an extracted entity with its label and text. + */ + public static class Entity { + public final String label; + public final String text; + public final int startToken; + public final int endToken; + + public Entity(String label, String text, int startToken, int endToken) { + this.label = label; + this.text = text; + this.startToken = startToken; + this.endToken = endToken; + } + } + + /** + * Extract entities from BIO-tagged sequence. + * Groups consecutive tokens with the same label into entities. + */ + public List<Entity> extractEntities() { + List<Entity> entities = new ArrayList<>(); + if (tokens == null || tokens.length == 0) { + return entities; + } + + String currentLabel = null; + int startIdx = -1; + StringBuilder currentText = new StringBuilder(); + + for (int i = 0; i < tokens.length; i++) { + String label = labels[i]; + String baseLabel = getBaseLabel(label); + + // Logic for Grobid-like labels (I-<label> is start, <label> is inside) + boolean isO = label.equals(TaggingLabels.OTHER_LABEL) || label.equals("O"); + boolean isBegin = label.startsWith(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX); + boolean isInside = !isO && !isBegin; + + if (isBegin || (isInside && !baseLabel.equals(currentLabel))) { + // Save previous entity if exists + if (currentLabel != null) { + entities.add(new Entity(currentLabel, currentText.toString().trim(), startIdx, i - 1)); + } + // Start new entity + currentLabel = baseLabel; + startIdx = i; + currentText = new StringBuilder(tokens[i]); + } else if (isInside && baseLabel.equals(currentLabel)) { + // Continue current entity + currentText.append(" ").append(tokens[i]); + } else if (isO) { + // End current entity if exists + if (currentLabel != null) { + entities.add(new Entity(currentLabel, currentText.toString().trim(), startIdx, i - 1)); + currentLabel = null; + startIdx = -1; + currentText = new StringBuilder(); + } + } + } + + // Don't forget last entity + if (currentLabel != null) { + entities.add(new Entity(currentLabel, currentText.toString().trim(), startIdx, tokens.length - 1)); + } + + return entities; + } + + /** + * Get base label without B-/I- prefix (also removes angle brackets). + */ + private String getBaseLabel(String label) { + String base = label; + if (label.startsWith(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX)) { // I- + base = label.substring(TaggingLabels.GROBID_START_ENTITY_LABEL_PREFIX.length()); + } else if (label.startsWith(TaggingLabels.IOB_START_ENTITY_LABEL_PREFIX)) { // B- + base = label.substring(TaggingLabels.IOB_START_ENTITY_LABEL_PREFIX.length()); + } else if (label.startsWith(TaggingLabels.IOB_INSIDE_LABEL_PREFIX)) { // I- (original IOB) + base = label.substring(TaggingLabels.IOB_INSIDE_LABEL_PREFIX.length()); + } + + // Remove angle brackets if present (e.g., <title> -> title) + if (base.startsWith("<") && base.endsWith(">")) { + return base.substring(1, base.length() - 1); + } + return base; + } + + /** + * Format entities as XML-like string. + * E.g., "<title>Analysis of 10,478 cancer genomesBen + * Kinnersley" + */ + public String toXmlString() { + List entities = extractEntities(); + StringBuilder sb = new StringBuilder(); + for (Entity entity : entities) { + sb.append("<").append(entity.label).append(">") + .append(entity.text) + .append(""); + } + return sb.toString(); + } + + public String toJson() { + List entities = extractEntities(); + + StringBuilder sb = new StringBuilder(); + sb.append("{\n"); + sb.append(" \"text\": \"").append(escapeJson(text)).append("\",\n"); + sb.append(" \"tokens\": ["); + for (int i = 0; i < tokens.length; i++) { + if (i > 0) + sb.append(", "); + sb.append("\"").append(escapeJson(tokens[i])).append("\""); + } + sb.append("],\n"); + sb.append(" \"labels\": ["); + for (int i = 0; i < labels.length; i++) { + if (i > 0) + sb.append(", "); + sb.append("\"").append(labels[i]).append("\""); + } + sb.append("],\n"); + + // Add XML-formatted entities + sb.append(" \"entitiesXml\": \"").append(escapeJson(toXmlString())).append("\",\n"); + + // Add structured entities list + sb.append(" \"entities\": ["); + for (int i = 0; i < entities.size(); i++) { + Entity e = entities.get(i); + if (i > 0) + sb.append(", "); + sb.append("\n {\"label\": \"").append(e.label) + .append("\", \"text\": \"").append(escapeJson(e.text)) + .append("\", \"start\": ").append(e.startToken) + .append(", \"end\": ").append(e.endToken).append("}"); + } + if (!entities.isEmpty()) { + sb.append("\n "); + } + sb.append("]\n}"); + return sb.toString(); + } + + private String escapeJson(String s) { + if (s == null) + return ""; + return s.replace("\\", "\\\\") + .replace("\"", "\\\"") + .replace("\n", "\\n") + .replace("\r", "\\r") + .replace("\t", "\\t"); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingRunner.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingRunner.java new file mode 100644 index 0000000000..59b9f2ad07 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingRunner.java @@ -0,0 +1,226 @@ +package org.grobid.core.engines.tagging.delft; + +import ai.onnxruntime.*; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.Closeable; +import java.nio.FloatBuffer; +import java.nio.LongBuffer; +import java.nio.file.Path; +import java.util.HashMap; +import java.util.Map; + +/** + * ONNX Runtime wrapper for running DeLFT encoder models. + */ +public class OnnxSequenceLabellingRunner implements Closeable { + + private static final Logger LOGGER = LoggerFactory.getLogger(OnnxSequenceLabellingRunner.class); + + private final OrtEnvironment env; + private final OrtSession session; + private final boolean hasFeatures; + + /** + * Load an ONNX model. + * + * @param modelPath Path to the .onnx file + */ + public OnnxSequenceLabellingRunner(Path modelPath) throws OrtException { + this.env = OrtEnvironment.getEnvironment(); + + OrtSession.SessionOptions options = new OrtSession.SessionOptions(); + options.setOptimizationLevel(OrtSession.SessionOptions.OptLevel.ALL_OPT); + + // Configure threading for optimal CPU inference performance + // Since GROBID manages concurrency at the worker level (e.g., 10 concurrent + // workers), + // use single-threaded inference per session to avoid CPU oversubscription + options.setIntraOpNumThreads(1); + + // interOpNumThreads: threads for parallel execution of multiple operators + // Set to 1 since GROBID manages concurrency at a higher level + options.setInterOpNumThreads(1); + + // Use sequential execution mode (vs parallel) since GROBID handles parallelism + options.setExecutionMode(OrtSession.SessionOptions.ExecutionMode.SEQUENTIAL); + + this.session = env.createSession(modelPath.toString(), options); + + // Check if model has features input + this.hasFeatures = session.getInputNames().contains("features_input"); + + LOGGER.info("Loaded ONNX model from {} (single-threaded, sequential mode)", modelPath); + LOGGER.info("Input names: {}", session.getInputNames()); + LOGGER.info("Output names: {}", session.getOutputNames()); + } + + /** + * Run inference to get emission scores. + * + * @param wordEmbeddings Word embeddings [batch, seq_len, embed_size] + * @param charIndices Character indices [batch, seq_len, max_char] + * @return Emission scores [batch, seq_len, num_tags] + */ + public float[][][] runInference(float[][][] wordEmbeddings, long[][][] charIndices) throws OrtException { + return runInference(wordEmbeddings, charIndices, null); + } + + /** + * Run inference with optional features. + * + * @param wordEmbeddings Word embeddings [batch, seq_len, embed_size] + * @param charIndices Character indices [batch, seq_len, max_char] + * @param featureIndices Optional feature indices [batch, seq_len, num_features] + * @return Emission scores [batch, seq_len, num_tags] + */ + public float[][][] runInference( + float[][][] wordEmbeddings, + long[][][] charIndices, + long[][][] featureIndices) throws OrtException { + + int batchSize = wordEmbeddings.length; + int seqLen = wordEmbeddings[0].length; + int embedSize = wordEmbeddings[0][0].length; + int maxChar = charIndices[0][0].length; + + // Create input tensors + Map inputs = new HashMap<>(); + + // Word embeddings tensor + float[] wordFlat = flatten3D(wordEmbeddings); + OnnxTensor wordTensor = OnnxTensor.createTensor(env, + FloatBuffer.wrap(wordFlat), + new long[] { batchSize, seqLen, embedSize }); + inputs.put("word_input", wordTensor); + + // Char indices tensor + long[] charFlat = flatten3DLong(charIndices); + OnnxTensor charTensor = OnnxTensor.createTensor(env, + LongBuffer.wrap(charFlat), + new long[] { batchSize, seqLen, maxChar }); + inputs.put("char_input", charTensor); + + // Features tensor (if model supports and provided) + if (hasFeatures && featureIndices != null) { + int numFeatures = featureIndices[0][0].length; + long[] featFlat = flatten3DLong(featureIndices); + OnnxTensor featTensor = OnnxTensor.createTensor(env, + LongBuffer.wrap(featFlat), + new long[] { batchSize, seqLen, numFeatures }); + inputs.put("features_input", featTensor); + } + + // Run inference + try (OrtSession.Result result = session.run(inputs)) { + // Get output tensor + OnnxTensor outputTensor = (OnnxTensor) result.get("emissions").get(); + + // Get shape [batch, seq_len, num_tags] + long[] shape = outputTensor.getInfo().getShape(); + int numTags = (int) shape[2]; + + // Copy output to array + float[] outputFlat = outputTensor.getFloatBuffer().array(); + + // Reshape to 3D + float[][][] emissions = new float[batchSize][seqLen][numTags]; + int idx = 0; + for (int b = 0; b < batchSize; b++) { + for (int s = 0; s < seqLen; s++) { + for (int t = 0; t < numTags; t++) { + emissions[b][s][t] = outputFlat[idx++]; + } + } + } + + return emissions; + } finally { + // Clean up input tensors + for (OnnxTensor tensor : inputs.values()) { + tensor.close(); + } + } + } + + /** + * Try to infer a fixed maximum sequence length from the ONNX model input tensor + * shape. + *

+ * This only works when the exported model declares a static seq_len dimension + * (e.g. [batch, 3000, embed]). If the model uses a dynamic dimension (often + * reported as -1 / symbolic), this method returns -1. + */ + public int inferMaxSequenceLength() { + try { + NodeInfo inputInfo = session.getInputInfo().get("word_input"); + if (inputInfo == null) { + return -1; + } + TensorInfo tensorInfo = (TensorInfo) inputInfo.getInfo(); + long[] shape = tensorInfo.getShape(); + if (shape == null || shape.length < 2) { + return -1; + } + long seqLen = shape[1]; + if (seqLen <= 0) { + return -1; + } + if (seqLen > Integer.MAX_VALUE) { + return -1; + } + return (int) seqLen; + } catch (Exception e) { + // Be conservative: inference should never fail because of this helper. + return -1; + } + } + + private float[] flatten3D(float[][][] arr) { + int d1 = arr.length; + int d2 = arr[0].length; + int d3 = arr[0][0].length; + float[] flat = new float[d1 * d2 * d3]; + int idx = 0; + for (int i = 0; i < d1; i++) { + for (int j = 0; j < d2; j++) { + for (int k = 0; k < d3; k++) { + flat[idx++] = arr[i][j][k]; + } + } + } + return flat; + } + + private long[] flatten3DLong(long[][][] arr) { + int d1 = arr.length; + int d2 = arr[0].length; + int d3 = arr[0][0].length; + long[] flat = new long[d1 * d2 * d3]; + int idx = 0; + for (int i = 0; i < d1; i++) { + for (int j = 0; j < d2; j++) { + for (int k = 0; k < d3; k++) { + flat[idx++] = arr[i][j][k]; + } + } + } + return flat; + } + + public boolean hasFeatures() { + return hasFeatures; + } + + @Override + public void close() { + try { + if (session != null) { + session.close(); + } + } catch (Exception e) { + LOGGER.warn("Error closing ONNX session", e); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/Preprocessor.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/Preprocessor.java new file mode 100644 index 0000000000..afd27bb76d --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/Preprocessor.java @@ -0,0 +1,298 @@ +package org.grobid.core.engines.tagging.delft; + +import com.google.gson.Gson; +import com.google.gson.JsonArray; +import com.google.gson.JsonElement; +import com.google.gson.JsonObject; +import org.grobid.core.analyzers.GrobidAnalyzer; +import org.grobid.core.layout.LayoutToken; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.FileReader; +import java.io.IOException; +import java.nio.file.Path; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; + +/** + * Preprocessor for converting text to model inputs. + * + * Uses GrobidAnalyzer for tokenization and converts to character indices. + * Supports feature preprocessing for BidLSTM_CRF_FEATURES models. + */ +public class Preprocessor { + + private static final Logger LOGGER = LoggerFactory.getLogger(Preprocessor.class); + + private final Map charVocab; + private final Map tagIndex; + private final int maxCharLength; + private final int padIndex; + private final int unkIndex; + + // Feature preprocessing support + private final List featuresIndices; + private final Map> featuresMapToIndex; + private final boolean hasFeatures; + + // Character encoding support - when false, return all-zero char indices + // This matches Python's DataLoader behavior when return_chars=False + private final boolean returnChars; + + /** + * Create preprocessor with vocabularies (no features, with char encoding). + */ + public Preprocessor(Map charVocab, Map tagIndex, int maxCharLength) { + this(charVocab, tagIndex, maxCharLength, null, null, true); + } + + /** + * Create preprocessor with vocabularies and features support. + */ + public Preprocessor(Map charVocab, Map tagIndex, int maxCharLength, + List featuresIndices, Map> featuresMapToIndex) { + this(charVocab, tagIndex, maxCharLength, featuresIndices, featuresMapToIndex, true); + } + + /** + * Create preprocessor with all options. + * + * @param returnChars If false, tokensToCharIndices returns all zeros (matching + * Python's return_chars=False) + */ + public Preprocessor(Map charVocab, Map tagIndex, int maxCharLength, + List featuresIndices, Map> featuresMapToIndex, boolean returnChars) { + this.charVocab = charVocab; + this.tagIndex = tagIndex; + this.maxCharLength = maxCharLength; + this.padIndex = charVocab.getOrDefault("", 0); + this.unkIndex = charVocab.getOrDefault("", 1); + this.featuresIndices = featuresIndices; + this.featuresMapToIndex = featuresMapToIndex; + this.hasFeatures = featuresIndices != null && !featuresIndices.isEmpty(); + this.returnChars = returnChars; + } + + /** + * Load preprocessor from vocab.json exported by Python. + */ + public static Preprocessor fromJson(Path vocabPath) throws IOException { + Gson gson = new Gson(); + try (FileReader reader = new FileReader(vocabPath.toFile())) { + JsonObject json = gson.fromJson(reader, JsonObject.class); + + // Parse char vocab + Map charVocabDouble = gson.fromJson(json.get("charVocab"), HashMap.class); + Map charVocab = new HashMap<>(); + for (Map.Entry entry : charVocabDouble.entrySet()) { + charVocab.put(entry.getKey(), entry.getValue().intValue()); + } + + // Parse tag index (index -> tag name) + Map tagIndexStr = gson.fromJson(json.get("tagIndex"), HashMap.class); + Map tagIndex = new HashMap<>(); + for (Map.Entry entry : tagIndexStr.entrySet()) { + tagIndex.put(Integer.parseInt(entry.getKey()), entry.getValue()); + } + + int maxCharLength = json.get("maxCharLength").getAsInt(); + + // Parse feature mappings if present + List featuresIndices = null; + Map> featuresMapToIndex = null; + + if (json.has("featuresIndices") && !json.get("featuresIndices").isJsonNull()) { + JsonArray indicesArray = json.getAsJsonArray("featuresIndices"); + featuresIndices = new ArrayList<>(); + for (JsonElement el : indicesArray) { + featuresIndices.add(el.getAsInt()); + } + + LOGGER.info("Loaded {} feature indices", featuresIndices.size()); + } + + if (json.has("featuresMapToIndex") && !json.get("featuresMapToIndex").isJsonNull()) { + JsonObject fmti = json.getAsJsonObject("featuresMapToIndex"); + featuresMapToIndex = new HashMap<>(); + + for (String featureIdxStr : fmti.keySet()) { + Integer featureIdx = Integer.parseInt(featureIdxStr); + JsonObject valueMap = fmti.getAsJsonObject(featureIdxStr); + Map innerMap = new HashMap<>(); + + for (String valueName : valueMap.keySet()) { + innerMap.put(valueName, valueMap.get(valueName).getAsInt()); + } + + featuresMapToIndex.put(featureIdx, innerMap); + } + + LOGGER.info("Loaded feature vocabulary with {} feature columns", featuresMapToIndex.size()); + } + + // Parse returnChars flag (defaults to true for backward compatibility) + boolean returnChars = true; + if (json.has("returnChars") && !json.get("returnChars").isJsonNull()) { + returnChars = json.get("returnChars").getAsBoolean(); + } + LOGGER.info("Loaded returnChars={}", returnChars); + + return new Preprocessor(charVocab, tagIndex, maxCharLength, featuresIndices, featuresMapToIndex, + returnChars); + } + } + + /** + * Tokenize text using GrobidAnalyzer. + * Filters out whitespace-only tokens to match Python DeLFT behavior. + * + * @param text Input text + * @return List of tokens (excluding whitespace-only tokens) + */ + public List tokenize(String text) { + List allTokens = GrobidAnalyzer.getInstance().tokenizeWithLayoutToken(text); + List filtered = new ArrayList<>(); + for (LayoutToken token : allTokens) { + String txt = token.getText(); + // Filter out whitespace-only tokens + if (txt != null && !txt.trim().isEmpty()) { + filtered.add(token); + } + } + return filtered; + } + + /** + * Convert tokens to character indices. + * + * If returnChars is false, returns all-zero array to match Python's + * DataLoader behavior when return_chars=False. + * + * @param tokens List of tokens + * @param seqLength Padded sequence length + * @return Character indices [seq_len][max_char_length] + */ + public long[][] tokensToCharIndices(List tokens, int seqLength) { + long[][] charIndices = new long[seqLength][maxCharLength]; + + // If returnChars is false, return all-zero array (matches Python's DataLoader) + if (!returnChars) { + return charIndices; + } + + for (int i = 0; i < Math.min(tokens.size(), seqLength); i++) { + String word = tokens.get(i).getText(); + for (int j = 0; j < Math.min(word.length(), maxCharLength); j++) { + String ch = String.valueOf(word.charAt(j)); + charIndices[i][j] = charVocab.getOrDefault(ch, unkIndex); + } + // Rest is padded with 0 (default) + } + + return charIndices; + } + + /** + * Convert tokens to string array. + */ + public String[] tokensToStrings(List tokens) { + String[] strings = new String[tokens.size()]; + for (int i = 0; i < tokens.size(); i++) { + strings[i] = tokens.get(i).getText(); + } + return strings; + } + + /** + * Convert tag indices to tag names. + */ + public String[] indicesToTags(int[] indices) { + String[] tags = new String[indices.length]; + for (int i = 0; i < indices.length; i++) { + tags[i] = tagIndex.getOrDefault(indices[i], "O"); + } + return tags; + } + + /** + * Create mask for valid tokens. + */ + public boolean[] createMask(int numTokens, int seqLength) { + boolean[] mask = new boolean[seqLength]; + for (int i = 0; i < Math.min(numTokens, seqLength); i++) { + mask[i] = true; + } + return mask; + } + + public int getMaxCharLength() { + return maxCharLength; + } + + public Map getTagIndex() { + return tagIndex; + } + + /** + * Check if this preprocessor supports features. + */ + public boolean hasFeatures() { + return hasFeatures; + } + + /** + * Get the number of features expected per token. + */ + public int getNumFeatures() { + return featuresIndices != null ? featuresIndices.size() : 0; + } + + /** + * Get the feature indices (column positions in training data). + */ + public List getFeaturesIndices() { + return featuresIndices; + } + + /** + * Convert feature strings to indices for ONNX model input. + * + * Features are provided as a 2D array: [numTokens][numFeatures] + * where each element is the feature value string (e.g., "ALLCAP", "LINESTART"). + * + * @param features Feature strings per token [numTokens][numFeatures] + * @param seqLength Padded sequence length + * @return Feature indices [seqLength][numFeatures] ready for ONNX model + */ + public long[][] tokensToFeatureIndices(String[][] features, int seqLength) { + if (!hasFeatures) { + return null; + } + + int numFeatures = featuresIndices.size(); + long[][] result = new long[seqLength][numFeatures]; + + int numTokens = Math.min(features.length, seqLength); + + for (int tokenIdx = 0; tokenIdx < numTokens; tokenIdx++) { + for (int featIdx = 0; featIdx < numFeatures; featIdx++) { + if (featIdx < features[tokenIdx].length) { + String featureValue = features[tokenIdx][featIdx]; + Integer originalColumnIdx = featuresIndices.get(featIdx); + + // Look up the index for this feature value using the original column vocabulary + Map valueMap = featuresMapToIndex.get(originalColumnIdx); + if (valueMap != null && featureValue != null) { + result[tokenIdx][featIdx] = valueMap.getOrDefault(featureValue, 0); + } + // Default is 0 (padding) + } + } + } + + return result; + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/WordEmbeddings.java b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/WordEmbeddings.java new file mode 100644 index 0000000000..a88bc2a514 --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/engines/tagging/delft/WordEmbeddings.java @@ -0,0 +1,480 @@ +package org.grobid.core.engines.tagging.delft; + +import com.google.common.cache.Cache; +import com.google.common.cache.CacheBuilder; +import org.lmdbjava.*; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.Closeable; +import java.io.IOException; +import java.nio.ByteBuffer; +import java.nio.ByteOrder; +import java.nio.charset.StandardCharsets; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.concurrent.ConcurrentHashMap; +import java.util.concurrent.Executors; +import java.util.concurrent.ScheduledExecutorService; +import java.util.concurrent.TimeUnit; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.concurrent.atomic.AtomicLong; + +/** + * Word embeddings lookup using LMDB database. + * + * Reads embeddings from LMDB where values are raw float32 arrays + * (little-endian). + * Use convert_lmdb_embeddings.py to convert from pickled numpy format. + * + * This class is a singleton per embeddings path - multiple models using the + * same embeddings (e.g., glove-840B) share a single LMDB connection. + * Use {@link #getInstance(Path, int)} to obtain instances. + */ +public class WordEmbeddings implements Closeable { + + private static final Logger LOGGER = LoggerFactory.getLogger(WordEmbeddings.class); + + // Singleton registry keyed by absolute path + private static final ConcurrentHashMap INSTANCES = new ConcurrentHashMap<>(); + + // Default max cache size: 200K entries (~240MB for 300-dim embeddings) + private static final int DEFAULT_CACHE_SIZE = 200_000; + + private final Env env; + private final Dbi dbi; + private final int embeddingSize; + private final float[] zeroVector; + private final AtomicInteger refCount = new AtomicInteger(0); // Track how many models are using this instance + + // LRU cache for embeddings - eliminates repeated LMDB lookups (using Guava) + private final Cache cache; + + // Instrumentation for LMDB access pattern analysis + private final AtomicLong totalLookups = new AtomicLong(); + private final AtomicLong cacheHits = new AtomicLong(); + private final AtomicLong totalLookupTimeNs = new AtomicLong(); + private final AtomicLong misses = new AtomicLong(); // Words not found in DB + private final ConcurrentHashMap uniqueWords = new ConcurrentHashMap<>(); + private final ScheduledExecutorService statsScheduler; + private final String dbName; + + /** + * Get a shared WordEmbeddings instance for the given path. + * + * Multiple models using the same embeddings path will share a single LMDB + * connection, reducing resource usage and reader slot contention. + * + * @param dbPath Path to the LMDB database directory + * @param embeddingSize Dimension of the embeddings + * @return Shared WordEmbeddings instance + * @throws IOException if the database cannot be opened + */ + public static WordEmbeddings getInstance(Path dbPath, int embeddingSize) throws IOException { + String key = dbPath.toAbsolutePath().toString(); + + WordEmbeddings instance = INSTANCES.get(key); + if (instance != null) { + instance.refCount.incrementAndGet(); + LOGGER.debug("Reusing existing WordEmbeddings instance for {} (refCount={})", + key, instance.refCount.get()); + return instance; + } + + // Double-checked locking for thread-safe lazy initialization + synchronized (INSTANCES) { + instance = INSTANCES.get(key); + if (instance == null) { + instance = new WordEmbeddings(dbPath, embeddingSize); + INSTANCES.put(key, instance); + LOGGER.info("Created new WordEmbeddings singleton for {}", key); + } + instance.refCount.incrementAndGet(); + return instance; + } + } + + /** + * Private constructor - use {@link #getInstance(Path, int)} instead. + * + * @param dbPath Path to the LMDB database directory + * @param embeddingSize Dimension of the embeddings + * @throws IOException if the database cannot be opened (missing path, LMDB + * error, or native library issue) + */ + private WordEmbeddings(Path dbPath, int embeddingSize) throws IOException { + this.embeddingSize = embeddingSize; + this.zeroVector = new float[embeddingSize]; + this.dbName = dbPath.getFileName().toString(); + + // Initialize Guava Cache with LRU eviction (max 200K entries ~240MB for + // 300-dim) + CacheBuilder cacheBuilder = CacheBuilder.newBuilder() + .maximumSize(DEFAULT_CACHE_SIZE); + + // Only enable cache statistics when debug logging is enabled (avoid overhead in + // production) + if (LOGGER.isDebugEnabled()) { + cacheBuilder.recordStats(); + } + this.cache = cacheBuilder.build(); + + // Check if path exists before trying to open + if (!Files.exists(dbPath)) { + throw new IOException("Embeddings database not found: " + dbPath.toAbsolutePath() + + "\nPlease provide a valid path to an LMDB embeddings database."); + } + if (!Files.isDirectory(dbPath)) { + throw new IOException("Embeddings path is not a directory: " + dbPath.toAbsolutePath() + + "\nLMDB databases are directories containing 'data.mdb' and 'lock.mdb' files."); + } + + try { + // Open LMDB environment with increased reader slots for high concurrency + this.env = Env.create() + .setMapSize(10_000_000_000L) // 10GB max + .setMaxReaders(512) // Support high concurrency (default is 126) + .setMaxDbs(1) + .open(dbPath.toFile()); + + // Open the default database + this.dbi = env.openDbi((String) null, DbiFlags.MDB_CREATE); + } catch (LmdbException e) { + throw new IOException("Failed to open LMDB database at " + dbPath.toAbsolutePath() + + ": " + e.getMessage(), e); + } catch (UnsatisfiedLinkError e) { + throw new IOException("LMDB native library failed to load. " + + "Ensure lmdbjava dependency includes native libraries for your platform. " + + "Error: " + e.getMessage(), e); + } + + // Validate that the database contains raw float32 format (not pickled numpy) + validateEmbeddingFormat(dbPath); + + // Start the stats logging scheduler only when debug logging is enabled + if (LOGGER.isDebugEnabled()) { + this.statsScheduler = Executors.newSingleThreadScheduledExecutor(r -> { + Thread t = new Thread(r, "lmdb-stats-" + dbName); + t.setDaemon(true); + return t; + }); + statsScheduler.scheduleAtFixedRate(this::logStats, 30, 30, TimeUnit.SECONDS); + LOGGER.info("Opened LMDB database at {} (debug stats logging enabled every 30s)", dbPath); + } else { + this.statsScheduler = null; + LOGGER.info("Opened LMDB database at {}", dbPath); + } + } + + /** + * Log accumulated statistics about LMDB access patterns. + * Called every 30 seconds by the stats scheduler. + */ + private void logStats() { + long lookups = totalLookups.get(); + if (lookups == 0) { + return; // Don't log if no activity + } + + long timeNs = totalLookupTimeNs.get(); + long missCount = misses.get(); + long hits = cacheHits.get(); + int uniqueCount = uniqueWords.size(); + long cacheSize = cache.size(); + + // Calculate metrics + double cacheHitRate = lookups > 0 ? 100.0 * hits / lookups : 0.0; + double dbHitRate = lookups > 0 ? 100.0 * (lookups - missCount) / lookups : 0.0; + double repeatRatio = uniqueCount > 0 ? (double) lookups / uniqueCount : 0.0; + long lmdbLookups = lookups - hits; + double avgLmdbTimeMs = lmdbLookups > 0 ? (timeNs / (double) lmdbLookups) / 1_000_000.0 : 0.0; + + LOGGER.debug("LMDB [{}] stats: {} lookups, cache hit: {}% ({} entries), " + + "DB hit: {}%, repeat ratio: {}x, avg LMDB lookup: {}ms", + dbName, lookups, + String.format("%.1f", cacheHitRate), cacheSize, + String.format("%.1f", dbHitRate), + String.format("%.1f", repeatRatio), + String.format("%.3f", avgLmdbTimeMs)); + } + + /** + * Look up embedding for a word. + * + * @param word The word to look up + * @return Embedding vector, or zero vector if not found + * @throws RuntimeException if LMDB database access fails + */ + public float[] getEmbedding(String word) { + // Normalize digits to "0" like Python's _normalize_num + String normalizedWord = normalizeNum(word); + + byte[] keyBytes = normalizedWord.getBytes(StandardCharsets.UTF_8); + ByteBuffer keyBuffer = ByteBuffer.allocateDirect(keyBytes.length); + keyBuffer.put(keyBytes).flip(); + + // Retry logic for LMDB BadReaderLockException under high concurrency + int maxRetries = 3; + int retryDelayMs = 10; + + for (int attempt = 0; attempt < maxRetries; attempt++) { + try (Txn txn = env.txnRead()) { + ByteBuffer valueBuffer = dbi.get(txn, keyBuffer); + + if (valueBuffer == null) { + // Word not found, return zero vector + return zeroVector.clone(); + } + + // Parse float array from raw bytes (little-endian float32) + valueBuffer.order(ByteOrder.LITTLE_ENDIAN); + float[] embedding = new float[embeddingSize]; + for (int i = 0; i < embeddingSize; i++) { + embedding[i] = valueBuffer.getFloat(); + } + return embedding; + } catch (Txn.BadReaderLockException e) { + if (attempt < maxRetries - 1) { + LOGGER.debug("LMDB reader lock contention (attempt {}), retrying", attempt + 1); + try { + Thread.sleep(retryDelayMs); + retryDelayMs *= 2; + } catch (InterruptedException ie) { + Thread.currentThread().interrupt(); + throw new RuntimeException("Interrupted during LMDB retry", ie); + } + } else { + throw new RuntimeException( + "LMDB error after " + maxRetries + " retries for word '" + word + "': " + e.getMessage(), + e); + } + } catch (LmdbException e) { + throw new RuntimeException( + "LMDB database error during embedding lookup for word '" + word + "': " + e.getMessage(), e); + } + } + + throw new RuntimeException("LMDB lookup failed after retries for word '" + word + "'"); + } + + /** + * Normalize digits in a word to "0" (matches Python's _normalize_num). + * This is needed because the model was trained with this normalization. + * + * @param word Input word + * @return Word with all digits replaced by "0" + */ + private String normalizeNum(String word) { + StringBuilder sb = new StringBuilder(); + for (char c : word.toCharArray()) { + if (Character.isDigit(c)) { + sb.append('0'); + } else { + sb.append(c); + } + } + return sb.toString(); + } + + /** + * Look up embeddings for a sequence of words. + * + * Uses a single LMDB read transaction for all lookups to avoid + * exhausting reader slots under high concurrency. + * + * @param words Array of words + * @return 2D array [seq_len][embedding_size] + * @throws RuntimeException if LMDB database access fails + */ + public float[][] getEmbeddings(String[] words) { + float[][] result = new float[words.length][embeddingSize]; + + // Retry logic for LMDB BadReaderLockException under high concurrency + int maxRetries = 3; + int retryDelayMs = 10; + + for (int attempt = 0; attempt < maxRetries; attempt++) { + try (Txn txn = env.txnRead()) { + for (int i = 0; i < words.length; i++) { + result[i] = getEmbeddingWithTxn(words[i], txn); + } + return result; // Success, return immediately + } catch (Txn.BadReaderLockException e) { + // Reader slot contention under high concurrency - retry after brief delay + if (attempt < maxRetries - 1) { + LOGGER.debug("LMDB reader lock contention (attempt {}), retrying after {}ms", + attempt + 1, retryDelayMs); + try { + Thread.sleep(retryDelayMs); + retryDelayMs *= 2; // Exponential backoff + } catch (InterruptedException ie) { + Thread.currentThread().interrupt(); + throw new RuntimeException("Interrupted during LMDB retry", ie); + } + } else { + throw new RuntimeException( + "LMDB database error after " + maxRetries + " retries: " + e.getMessage(), e); + } + } catch (LmdbException e) { + throw new RuntimeException( + "LMDB database error during batch embedding lookup: " + e.getMessage(), e); + } + } + + // Should not reach here, but satisfy compiler + throw new RuntimeException("LMDB lookup failed after retries"); + } + + /** + * Look up embedding for a word using an existing transaction. + * + * @param word The word to look up + * @param txn Active read transaction + * @return Embedding vector, or zero vector if not found + */ + private float[] getEmbeddingWithTxn(String word, Txn txn) { + // Normalize digits to "0" like Python's _normalize_num + String normalizedWord = normalizeNum(word); + + // Track lookups and unique words + totalLookups.incrementAndGet(); + uniqueWords.putIfAbsent(normalizedWord, Boolean.TRUE); + + // Check cache first - avoids LMDB disk I/O for repeated words + float[] cached = cache.getIfPresent(normalizedWord); + if (cached != null) { + cacheHits.incrementAndGet(); + return cached; // Return cached copy (no clone needed - embeddings are read-only) + } + + // Cache miss - look up in LMDB + long startNs = System.nanoTime(); + + byte[] keyBytes = normalizedWord.getBytes(StandardCharsets.UTF_8); + ByteBuffer keyBuffer = ByteBuffer.allocateDirect(keyBytes.length); + keyBuffer.put(keyBytes).flip(); + + ByteBuffer valueBuffer = dbi.get(txn, keyBuffer); + + totalLookupTimeNs.addAndGet(System.nanoTime() - startNs); + + if (valueBuffer == null) { + // Word not found, cache and return zero vector + misses.incrementAndGet(); + float[] zero = zeroVector.clone(); + cache.put(normalizedWord, zero); + return zero; + } + + // Parse float array from raw bytes (little-endian float32) + valueBuffer.order(ByteOrder.LITTLE_ENDIAN); + float[] embedding = new float[embeddingSize]; + for (int i = 0; i < embeddingSize; i++) { + embedding[i] = valueBuffer.getFloat(); + } + + // Store in cache for future lookups + cache.put(normalizedWord, embedding); + return embedding; + } + + /** + * Check if a word exists in the database. + * + * @throws RuntimeException if LMDB database access fails + */ + public boolean contains(String word) { + byte[] keyBytes = word.getBytes(StandardCharsets.UTF_8); + ByteBuffer keyBuffer = ByteBuffer.allocateDirect(keyBytes.length); + keyBuffer.put(keyBytes).flip(); + + try (Txn txn = env.txnRead()) { + return dbi.get(txn, keyBuffer) != null; + } catch (LmdbException e) { + throw new RuntimeException("LMDB database error checking word '" + word + "': " + e.getMessage(), e); + } + } + + public int getEmbeddingSize() { + return embeddingSize; + } + + /** + * Validate that the embeddings database contains raw float32 format. + * + * If the database contains pickled numpy arrays (the old DeLFT format), + * the bytes will be interpreted as garbage floats with extreme values. + * This validation fails fast at startup with a clear error message. + * + * @param dbPath Path to the database (for error messages) + * @throws IOException if validation fails + */ + private void validateEmbeddingFormat(Path dbPath) throws IOException { + // Common test words that should exist in any GloVe/word2vec vocabulary + String[] testWords = { "the", "and", "of", "to", "in" }; + final float MAX_VALID_VALUE = 10.0f; // GloVe values are typically < 5 + + for (String testWord : testWords) { + if (contains(testWord)) { + float[] embedding = getEmbedding(testWord); + + for (int i = 0; i < embedding.length; i++) { + float value = embedding[i]; + + if (Float.isNaN(value) || Float.isInfinite(value) || Math.abs(value) > MAX_VALID_VALUE) { + close(); // Clean up before throwing + throw new IOException( + "Embeddings database at " + dbPath.toAbsolutePath() + " appears to contain " + + "pickled numpy format instead of raw float32.\n" + + "Found invalid embedding value for word '" + testWord + "': " + + (Float.isNaN(value) ? "NaN" : Float.isInfinite(value) ? "Infinity" : value) + + " at index " + i + ".\n" + + "Please regenerate embeddings using:\n" + + " python3 grobid-home/scripts/preload_embeddings.py --embedding glove-840B"); + } + } + + LOGGER.debug("Embeddings format validation passed for word '{}'", testWord); + return; // Validation passed for one word, that's enough + } + } + + LOGGER.warn("Could not validate embeddings format - none of the test words found in database"); + } + + @Override + public void close() { + // Reference counting: only close if this is the last reference + int remaining = refCount.decrementAndGet(); + if (remaining > 0) { + LOGGER.debug("WordEmbeddings [{}] close called, but {} references remain", dbName, remaining); + return; + } + + // Remove from singleton registry + INSTANCES.values().remove(this); + LOGGER.info("Closing WordEmbeddings singleton for {}", dbName); + + // Shutdown stats scheduler first + if (statsScheduler != null) { + statsScheduler.shutdown(); + try { + if (!statsScheduler.awaitTermination(5, TimeUnit.SECONDS)) { + statsScheduler.shutdownNow(); + } + } catch (InterruptedException e) { + statsScheduler.shutdownNow(); + Thread.currentThread().interrupt(); + } + // Log final stats before closing + logStats(); + } + + if (dbi != null) { + dbi.close(); + } + if (env != null) { + env.close(); + } + } +} diff --git a/grobid-core/src/main/java/org/grobid/core/features/FeaturesVectorHeader.java b/grobid-core/src/main/java/org/grobid/core/features/FeaturesVectorHeader.java index 2ef1859577..361cb02edb 100755 --- a/grobid-core/src/main/java/org/grobid/core/features/FeaturesVectorHeader.java +++ b/grobid-core/src/main/java/org/grobid/core/features/FeaturesVectorHeader.java @@ -52,6 +52,94 @@ public class FeaturesVectorHeader { public boolean largerThanAverageFont = false; //public boolean superscript = false; + public static FeaturesVectorHeader fromLayoutToken(LayoutToken token) { + FeaturesVectorHeader features = new FeaturesVectorHeader(); + FeatureFactory featureFactory = FeatureFactory.getInstance(); + + String text = token.getText(); + features.token = token; + features.string = text; + + Matcher m0 = featureFactory.isPunct.matcher(text); + + if (m0.find()) { + features.punctType = "PUNCT"; + } + if (text.equals("(") || text.equals("[")) { + features.punctType = "OPENBRACKET"; + + } else if (text.equals(")") || text.equals("]")) { + features.punctType = "ENDBRACKET"; + + } else if (text.equals(".")) { + features.punctType = "DOT"; + + } else if (text.equals(",")) { + features.punctType = "COMMA"; + + } else if (text.equals("-")) { + features.punctType = "HYPHEN"; + + } else if (text.equals("\"") || text.equals("\'") || text.equals("`")) { + features.punctType = "QUOTE"; + } + + if (text.length() == 1) { + features.singleChar = true; + } + + if (Character.isUpperCase(text.charAt(0))) { + features.capitalisation = "INITCAP"; + } + + if (featureFactory.test_all_capital(text)) { + features.capitalisation = "ALLCAP"; + } + + if (featureFactory.test_digit(text)) { + features.digit = "CONTAINSDIGITS"; + } + + Matcher m = featureFactory.isDigit.matcher(text); + if (m.find()) { + features.digit = "ALLDIGIT"; + } + + if (featureFactory.test_common(text)) { + features.commonName = true; + } + + if (featureFactory.test_names(text)) { + features.properName = true; + } + + if (featureFactory.test_month(text)) { + features.month = true; + } + + Matcher m2 = featureFactory.year.matcher(text); + if (m2.find()) { + features.year = true; + } + + if (token.isBold()) + features.bold = true; + + if (token.isItalic()) + features.italic = true; + + if (features.capitalisation == null) + features.capitalisation = "NOCAPS"; + + if (features.digit == null) + features.digit = "NODIGIT"; + + if (features.punctType == null) + features.punctType = "NOPUNCT"; + + return features; + } + public String printVector() { if (string == null) return null; if (string.length() == 0) return null; diff --git a/grobid-core/src/main/java/org/grobid/core/jni/DeLFTClassifierModel.java b/grobid-core/src/main/java/org/grobid/core/jni/DeLFTClassifierModel.java index 21f2255b12..c530a8ffe3 100644 --- a/grobid-core/src/main/java/org/grobid/core/jni/DeLFTClassifierModel.java +++ b/grobid-core/src/main/java/org/grobid/core/jni/DeLFTClassifierModel.java @@ -18,10 +18,11 @@ import java.util.regex.Matcher; import java.util.regex.Pattern; -public class DeLFTClassifierModel { +public class DeLFTClassifierModel implements org.grobid.core.engines.tagging.GenericClassifier { public static final Logger LOGGER = LoggerFactory.getLogger(DeLFTClassifierModel.class); - // Exploit JNI CPython interpreter to execute load and execute a DeLFT deep learning model + // Exploit JNI CPython interpreter to execute load and execute a DeLFT deep + // learning model private String modelName; private String architecture; @@ -29,8 +30,10 @@ public DeLFTClassifierModel(String model, String architecture) { this.modelName = model; this.architecture = architecture; try { - LOGGER.info("Loading DeLFT classification model for " + this.modelName + " in " + GrobidProperties.getInstance().getModelPath()); - JEPThreadPoolClassifier.getInstance().run(new InitModel(this.modelName, GrobidProperties.getInstance().getModelPath(), this.architecture)); + LOGGER.info("Loading DeLFT classification model for " + this.modelName + " in " + + GrobidProperties.getInstance().getModelPath()); + JEPThreadPoolClassifier.getInstance().run( + new InitModel(this.modelName, GrobidProperties.getInstance().getModelPath(), this.architecture)); } catch (InterruptedException | RuntimeException e) { LOGGER.error("DeLFT model " + this.modelName + " initialization failed", e); } @@ -60,12 +63,12 @@ public void run() { GrobidProperties.getInstance(); if (GrobidProperties.getDelftRuntimeMaxSequenceLength(this.modelName) != -1) { jep.eval(this.modelName + ".config.max_sequence_length=" + - GrobidProperties.getDelftRuntimeMaxSequenceLength(this.modelName)); + GrobidProperties.getDelftRuntimeMaxSequenceLength(this.modelName)); } if (GrobidProperties.getDelftRuntimeBatchSize(this.modelName) != -1) { jep.eval(this.modelName + ".config.batch_size=" + - GrobidProperties.getDelftRuntimeBatchSize(this.modelName)); + GrobidProperties.getDelftRuntimeBatchSize(this.modelName)); } } catch (JepException e) { @@ -80,32 +83,30 @@ private class ClassificationTask implements Callable { private String modelName; public ClassificationTask(String modelName, List data) { - //System.out.println("label thread: " + Thread.currentThread().getId()); + // System.out.println("label thread: " + Thread.currentThread().getId()); this.modelName = modelName; this.data = data; } private void setJepStringValueWithFileFallback( - Jep jep, String name, List values - ) throws JepException, IOException { + Jep jep, String name, List values) throws JepException, IOException { try { jep.set(name, values); - // convert PyJList to a normal python list (necessary for Hugging Face transformer tokenizer input) + // convert PyJList to a normal python list (necessary for Hugging Face + // transformer tokenizer input) jep.eval(name + " = list(" + name + ")"); } catch (JepException e) { // we have normally the Java List as a PyJList in python, which should - // be equivalent to a normal python list + // be equivalent to a normal python list File tempFile = IOUtilities.newTempFile(name, ".data"); LOGGER.debug( - "Falling back to file {} due to exception: {}", - tempFile, e.toString() - ); + "Falling back to file {} due to exception: {}", + tempFile, e.toString()); IOUtilities.writeListInFile(tempFile.getAbsolutePath(), values, "|"); jep.eval("from pathlib import Path"); jep.eval( - name + " = Path('" + tempFile.getAbsolutePath() + - "').read_text(encoding='utf-8').split(\"|\")" - ); + name + " = Path('" + tempFile.getAbsolutePath() + + "').read_text(encoding='utf-8').split(\"|\")"); tempFile.delete(); } } @@ -119,8 +120,10 @@ public String call() { this.setJepStringValueWithFileFallback(jep, "input", this.data); String model_variable = this.modelName.replace("-", "_"); jep.eval("jsondict = " + model_variable + ".predict(input, 'json', use_main_thread_only=True)"); - //jep.eval("print(json.dumps(jsondict, sort_keys=False, indent=4, ensure_ascii=False))"); - Object objectResult = jep.getValue("json.dumps(jsondict, sort_keys=True, indent=4, ensure_ascii=False)"); + // jep.eval("print(json.dumps(jsondict, sort_keys=False, indent=4, + // ensure_ascii=False))"); + Object objectResult = jep + .getValue("json.dumps(jsondict, sort_keys=True, indent=4, ensure_ascii=False)"); results = (String) objectResult; @@ -139,7 +142,7 @@ public String call() { LOGGER.error("DeLFT model classification via JEP failed", e); } } - //System.out.println(labelledData.toString()); + // System.out.println(labelledData.toString()); return results; } } @@ -161,8 +164,10 @@ public String classify(List data) { } /** - * Training via JNI CPython interpreter (JEP). It appears that after some epochs, the JEP thread - * usually hangs... Possibly issues with IO threads at the level of JEP (output not consumed because + * Training via JNI CPython interpreter (JEP). It appears that after some + * epochs, the JEP thread + * usually hangs... Possibly issues with IO threads at the level of JEP (output + * not consumed because * of \r and no end of line?). */ public static void trainJNI(String modelName, File trainingData, File outputModel) { @@ -170,7 +175,7 @@ public static void trainJNI(String modelName, File trainingData, File outputMode LOGGER.info("Train DeLFT classification model " + modelName + "..."); GrobidProperties.getInstance(); JEPThreadPoolClassifier.getInstance().run( - new TrainTask(modelName, trainingData, GrobidProperties.getModelPath())); + new TrainTask(modelName, trainingData, GrobidProperties.getModelPath())); } catch (InterruptedException e) { LOGGER.error("Train DeLFT classification model " + modelName + " task failed", e); } @@ -184,8 +189,9 @@ private static class TrainTask implements Runnable { private boolean incremental; public TrainTask(String modelName, File trainPath, File modelPath) { - //public TrainTask(String modelName, File trainPath, File modelPath, String architecture, boolean incremental) { - //System.out.println("train thread: " + Thread.currentThread().getId()); + // public TrainTask(String modelName, File trainPath, File modelPath, String + // architecture, boolean incremental) { + // System.out.println("train thread: " + Thread.currentThread().getId()); this.modelName = modelName; this.trainPath = trainPath; this.modelPath = modelPath; @@ -199,7 +205,8 @@ public void run() { try { // load data // to be reviewed for classification - jep.eval("x_all, y_all, f_all = load_data_and_labels_crf_file('" + this.trainPath.getAbsolutePath() + "')"); + jep.eval("x_all, y_all, f_all = load_data_and_labels_crf_file('" + this.trainPath.getAbsolutePath() + + "')"); jep.eval("x_train, x_valid, y_train, y_valid = train_test_split(x_all, y_all, test_size=0.1)"); jep.eval("print(len(x_train), 'train sequences')"); jep.eval("print(len(x_valid), 'validation sequences')"); @@ -213,38 +220,41 @@ public void run() { String localArgs = ""; if (GrobidProperties.getDelftTrainingMaxSequenceLength(this.modelName) != -1) localArgs += ", maxlen=" + - GrobidProperties.getDelftTrainingMaxSequenceLength(this.modelName); + GrobidProperties.getDelftTrainingMaxSequenceLength(this.modelName); if (GrobidProperties.getDelftTrainingBatchSize(this.modelName) != -1) localArgs += ", batch_size=" + - GrobidProperties.getDelftTrainingBatchSize(this.modelName); + GrobidProperties.getDelftTrainingBatchSize(this.modelName); if (GrobidProperties.getDelftTranformer(modelName) != null) { localArgs += ", transformer=" + - GrobidProperties.getDelftTranformer(modelName); + GrobidProperties.getDelftTranformer(modelName); } // init model to be trained if (this.architecture == null) { jep.eval("model = Classifier('" + this.modelName + - "', max_epoch=100, recurrent_dropout=0.50, embeddings_name='glove-840B', use_ELMo=" + useELMo + localArgs + ")"); + "', max_epoch=100, recurrent_dropout=0.50, embeddings_name='glove-840B', use_ELMo=" + + useELMo + localArgs + ")"); } else { jep.eval("model = Classifier('" + this.modelName + - "', max_epoch=100, recurrent_dropout=0.50, embeddings_name='glove-840B', use_ELMo=" + useELMo + localArgs + - ", architecture='" + architecture + "')"); + "', max_epoch=100, recurrent_dropout=0.50, embeddings_name='glove-840B', use_ELMo=" + + useELMo + localArgs + + ", architecture='" + architecture + "')"); } // actual training if (incremental) { // if incremental training, we need to load the existing model if (this.modelPath != null && - this.modelPath.exists() && - !this.modelPath.isDirectory()) { + this.modelPath.exists() && + !this.modelPath.isDirectory()) { jep.eval("model.load('" + this.modelPath.getAbsolutePath() + "')"); jep.eval("model.train(x_train, y_train, x_valid, y_valid, incremental=True)"); } else { - throw new GrobidException("the path to the model to be used for starting incremental training is invalid: " + - this.modelPath.getAbsolutePath()); + throw new GrobidException( + "the path to the model to be used for starting incremental training is invalid: " + + this.modelPath.getAbsolutePath()); } } else jep.eval("model.train(x_train, y_train, x_valid, y_valid)"); @@ -276,18 +286,20 @@ public void run() { } /** - * Train with an external process rather than with JNI, this approach appears to be more stable for the - * training process (JNI approach hangs after a while) and does not raise any runtime/integration issues. + * Train with an external process rather than with JNI, this approach appears to + * be more stable for the + * training process (JNI approach hangs after a while) and does not raise any + * runtime/integration issues. */ public static void train(String modelName, File trainingData, File outputModel) { try { LOGGER.info("Train DeLFT model " + modelName + "..."); List command = Arrays.asList("python3", - "dataseerClassifier.py", - modelName, - "train", - "--input", trainingData.getAbsolutePath(), - "--output", GrobidProperties.getInstance().getModelPath().getAbsolutePath()); + "dataseerClassifier.py", + modelName, + "train", + "--input", trainingData.getAbsolutePath(), + "--output", GrobidProperties.getInstance().getModelPath().getAbsolutePath()); if (GrobidProperties.getInstance().useELMo(modelName)) { command.add("--use-ELMo"); } @@ -296,14 +308,13 @@ public static void train(String modelName, File trainingData, File outputModel) File delftPath = new File(GrobidProperties.getInstance().getDeLFTFilePath()); pb.directory(delftPath); Process process = pb.start(); - //pb.inheritIO(); - CustomStreamGobbler customStreamGobbler = - new CustomStreamGobbler(process.getInputStream(), System.out); + // pb.inheritIO(); + CustomStreamGobbler customStreamGobbler = new CustomStreamGobbler(process.getInputStream(), System.out); Executors.newSingleThreadExecutor().submit(customStreamGobbler); SimpleStreamGobbler streamGobbler = new SimpleStreamGobbler(process.getErrorStream(), System.err::println); Executors.newSingleThreadExecutor().submit(streamGobbler); int exitCode = process.waitFor(); - //assert exitCode == 0; + // assert exitCode == 0; } catch (IOException e) { LOGGER.error("IO error when training DeLFT classification model " + modelName, e); } catch (InterruptedException e) { @@ -335,8 +346,10 @@ public void run() { String model_variable = null; try { model_variable = this.modelName.replace("-", "_"); - // We don't close the JEP instance here because it might be reused by other models - // The JEP instance will be closed when the application shuts down or when explicitly requested + // We don't close the JEP instance here because it might be reused by other + // models + // The JEP instance will be closed when the application shuts down or when + // explicitly requested } catch (JepException e) { LOGGER.error("Closing DeLFT classification model failed", e); } finally { @@ -363,12 +376,13 @@ public SimpleStreamGobbler(InputStream inputStream, Consumer consumer) { @Override public void run() { new BufferedReader(new InputStreamReader(inputStream)).lines() - .forEach(consumer); + .forEach(consumer); } } /** - * This is a custom gobbler that reproduces correctly the Keras training progress bar + * This is a custom gobbler that reproduces correctly the Keras training + * progress bar * by injecting a \r for progress line updates. */ private static class CustomStreamGobbler implements Runnable { diff --git a/grobid-core/src/main/java/org/grobid/core/main/LibraryLoader.java b/grobid-core/src/main/java/org/grobid/core/main/LibraryLoader.java index 7b8e5d933d..8a638709a1 100755 --- a/grobid-core/src/main/java/org/grobid/core/main/LibraryLoader.java +++ b/grobid-core/src/main/java/org/grobid/core/main/LibraryLoader.java @@ -40,38 +40,44 @@ public static void load() { LOGGER.debug(getLibraryFolder()); Set distinctModels = GrobidProperties.getInstance().getDistinctModels(); - for(GrobidCRFEngine distinctModel : distinctModels) { + for (GrobidCRFEngine distinctModel : distinctModels) { if (distinctModel != GrobidCRFEngine.CRFPP && - distinctModel != GrobidCRFEngine.WAPITI && - distinctModel != GrobidCRFEngine.DELFT) { + distinctModel != GrobidCRFEngine.WAPITI && + distinctModel != GrobidCRFEngine.DELFT && + distinctModel != GrobidCRFEngine.ONNX && + distinctModel != GrobidCRFEngine.DUMMY) { throw new IllegalStateException("Unsupported sequence labelling engine: " + distinctModel); } } File libraryFolder = new File(getLibraryFolder()); if (!libraryFolder.exists() || !libraryFolder.isDirectory()) { - LOGGER.error("Unable to find a native sequence labelling library: Folder " + libraryFolder + " does not exist"); + LOGGER.error("Unable to find a native sequence labelling library: Folder " + libraryFolder + + " does not exist"); throw new RuntimeException( - "Unable to find a native sequence labelling library: Folder " + libraryFolder + " does not exist"); + "Unable to find a native sequence labelling library: Folder " + libraryFolder + + " does not exist"); } if (CollectionUtils.containsAny(distinctModels, Collections.singletonList(GrobidCRFEngine.CRFPP))) { - File[] files = libraryFolder.listFiles(file -> file.getName().toLowerCase().startsWith(CRFPP_NATIVE_LIB_NAME)); + File[] files = libraryFolder + .listFiles(file -> file.getName().toLowerCase().startsWith(CRFPP_NATIVE_LIB_NAME)); if (ArrayUtils.isEmpty(files)) { LOGGER.error("Unable to find a native CRF++ library: No files starting with " - + CRFPP_NATIVE_LIB_NAME - + " are in folder " + libraryFolder); - throw new RuntimeException( - "Unable to find a native CRF++ library: No files starting with " + CRFPP_NATIVE_LIB_NAME + " are in folder " + libraryFolder); + throw new RuntimeException( + "Unable to find a native CRF++ library: No files starting with " + + CRFPP_NATIVE_LIB_NAME + + " are in folder " + libraryFolder); } if (files.length > 1) { - LOGGER.error("Unable to load a native CRF++ library: More than 1 library exists in " + libraryFolder); + LOGGER.error( + "Unable to load a native CRF++ library: More than 1 library exists in " + libraryFolder); throw new RuntimeException( - "Unable to load a native CRF++ library: More than 1 library exists in " + libraryFolder); + "Unable to load a native CRF++ library: More than 1 library exists in " + libraryFolder); } String libPath = files[0].getAbsolutePath(); @@ -82,11 +88,11 @@ public static void load() { } catch (Exception e) { LOGGER.error("Unable to load a native CRF++ library, although it was found under path " + libPath); throw new RuntimeException( - "Unable to load a native CRF++ library, although it was found under path " + libPath, e); + "Unable to load a native CRF++ library, although it was found under path " + libPath, e); } } - - if (CollectionUtils.containsAny(distinctModels, Collections.singletonList(GrobidCRFEngine.WAPITI))) { + + if (CollectionUtils.containsAny(distinctModels, Collections.singletonList(GrobidCRFEngine.WAPITI))) { File[] wapitiLibFiles = libraryFolder.listFiles(new FilenameFilter() { @Override public boolean accept(File dir, String name) { @@ -99,10 +105,13 @@ public boolean accept(File dir, String name) { } else { LOGGER.info("Loading Wapiti native library..."); if (CollectionUtils.containsAny(distinctModels, Collections.singletonList(GrobidCRFEngine.DELFT))) { - // if DeLFT will be used, we must not load libstdc++, it would create a conflict with tensorflow libstdc++ version + // if DeLFT will be used, we must not load libstdc++, it would create a conflict + // with tensorflow libstdc++ version // so we temporary rename the lib so that it is not loaded in this case - // note that we know that, in this case, the local lib can be ignored because as DeFLT and tensorflow are installed - // we are sure that a compatible libstdc++ lib is installed on the system and can be dynamically loaded + // note that we know that, in this case, the local lib can be ignored because as + // DeFLT and tensorflow are installed + // we are sure that a compatible libstdc++ lib is installed on the system and + // can be dynamically loaded String libstdcppPath = libraryFolder.getAbsolutePath() + File.separator + "libstdc++.so.6"; File libstdcppFile = new File(libstdcppPath); @@ -123,18 +132,22 @@ public boolean accept(File dir, String name) { } finally { if (CollectionUtils.containsAny(distinctModels, Arrays.asList(GrobidCRFEngine.DELFT))) { // restore libstdc++ - String libstdcppPathNew = libraryFolder.getAbsolutePath() + File.separator + "libstdc++.so.6.new"; + String libstdcppPathNew = libraryFolder.getAbsolutePath() + File.separator + + "libstdc++.so.6.new"; File libstdcppFileNew = new File(libstdcppPathNew); if (libstdcppFileNew.exists()) { - File libstdcppFile = new File(libraryFolder.getAbsolutePath() + File.separator + "libstdc++.so.6"); + File libstdcppFile = new File( + libraryFolder.getAbsolutePath() + File.separator + "libstdc++.so.6"); libstdcppFileNew.renameTo(libstdcppFile); } // restore libgcc - String libgccPathNew = libraryFolder.getAbsolutePath() + File.separator + "libgcc_s.so.1.new"; + String libgccPathNew = libraryFolder.getAbsolutePath() + File.separator + + "libgcc_s.so.1.new"; File libgccFileNew = new File(libgccPathNew); if (libgccFileNew.exists()) { - File libgccFile = new File(libraryFolder.getAbsolutePath() + File.separator + "libgcc_s.so.1"); + File libgccFile = new File( + libraryFolder.getAbsolutePath() + File.separator + "libgcc_s.so.1"); libgccFileNew.renameTo(libgccFile); } } @@ -144,8 +157,10 @@ public boolean accept(File dir, String name) { if (CollectionUtils.containsAny(distinctModels, Collections.singletonList(GrobidCRFEngine.DELFT))) { LOGGER.info("Loading JEP native library for DeLFT... " + libraryFolder.getAbsolutePath()); - // actual loading will be made at JEP initialization, so we just need to add the path in the - // java.library.path (JEP will anyway try to load from java.library.path, so explicit file + // actual loading will be made at JEP initialization, so we just need to add the + // path in the + // java.library.path (JEP will anyway try to load from java.library.path, so + // explicit file // loading here will not help) try { @@ -192,8 +207,8 @@ public static void addLibraryPath(String pathToAdd) throws Exception { public static String getLibraryFolder() { GrobidProperties.getInstance(); - return String.format("%s" + File.separator + "%s", - GrobidProperties.getNativeLibraryPath().getAbsolutePath(), - Utilities.getOsNameAndArch()); + return String.format("%s" + File.separator + "%s", + GrobidProperties.getNativeLibraryPath().getAbsolutePath(), + Utilities.getOsNameAndArch()); } } diff --git a/grobid-core/src/main/java/org/grobid/core/utilities/GrobidConfig.java b/grobid-core/src/main/java/org/grobid/core/utilities/GrobidConfig.java index 986c2645e4..b3e1216c8c 100644 --- a/grobid-core/src/main/java/org/grobid/core/utilities/GrobidConfig.java +++ b/grobid-core/src/main/java/org/grobid/core/utilities/GrobidConfig.java @@ -3,7 +3,7 @@ import java.util.List; /** - * This class is a bean for the YAML configuation of the GROBID instance. + * This class is a bean for the YAML configuation of the GROBID instance. * */ public class GrobidConfig { @@ -21,12 +21,12 @@ public static class GrobidParameters { public String languageDetectorFactory; public String sentenceDetectorFactory; - - public int concurrency = 10; + + public int concurrency = 10; public int poolMaxWait = 1; - - public DelftParameters delft; - public WapitiParameters wapiti; + + public DelftParameters delft; + public WapitiParameters wapiti; public List models; } @@ -61,7 +61,7 @@ public static class HostParameters { public String url; public int timeoutSec = 60; } - + public static class DelftParameters { /** * Generic parameters relative to the DeLFT engine @@ -107,11 +107,21 @@ public static class DelftModelParameterSet { public int batch_size = -1; } - public static class ModelParameters { - public String name; /* name of model */ - public String engine; /* value wapiti or delft */ + public static class OnnxModelParameters { + /** + * Parameters relative to a specific ONNX model + */ + public String architecture; + public int max_sequence_length = -1; + public int batch_size = -1; + } + + public static class ModelParameters { + public String name; /* name of model */ + public String engine; /* value wapiti, delft, or onnx */ public WapitiModelParameters wapiti; public DelftModelParameters delft; + public OnnxModelParameters onnx; } } \ No newline at end of file diff --git a/grobid-core/src/main/java/org/grobid/core/utilities/GrobidProperties.java b/grobid-core/src/main/java/org/grobid/core/utilities/GrobidProperties.java index a9d44a8508..62a391706b 100644 --- a/grobid-core/src/main/java/org/grobid/core/utilities/GrobidProperties.java +++ b/grobid-core/src/main/java/org/grobid/core/utilities/GrobidProperties.java @@ -30,14 +30,18 @@ import com.fasterxml.jackson.databind.DeserializationFeature; /** - * This class provide methods to set/load/access grobid config value from a yaml config file loaded + * This class provide methods to set/load/access grobid config value from a yaml + * config file loaded * in the class {@link GrobidConfig}. * - * New yaml parameters and former properties should be equivalent via this class. We keep the - * class name "GrobidProperties" for compatibility with Grobid modules and other Java applications + * New yaml parameters and former properties should be equivalent via this + * class. We keep the + * class name "GrobidProperties" for compatibility with Grobid modules and other + * Java applications * using Grobid as a library. * - * to be done: having parameters that can be overridden by a system property having a compatible name. + * to be done: having parameters that can be overridden by a system property + * having a compatible name. */ public class GrobidProperties { public static final Logger LOGGER = LoggerFactory.getLogger(GrobidProperties.class); @@ -82,7 +86,8 @@ public class GrobidProperties { private static String GROBID_VERSION = null; /** - * Returns an instance of {@link GrobidProperties} object. If no one is set, then + * Returns an instance of {@link GrobidProperties} object. If no one is set, + * then * it creates one */ public static GrobidProperties getInstance() { @@ -94,7 +99,8 @@ public static GrobidProperties getInstance() { } /** - * Returns an instance of {@link GrobidProperties} object based on a custom grobid-home directory. + * Returns an instance of {@link GrobidProperties} object based on a custom + * grobid-home directory. * If no one is set, then it creates one. */ public static GrobidProperties getInstance(GrobidHomeFinder grobidHomeFinder) { @@ -172,14 +178,15 @@ public static void setGrobidHome(final String pGROBID_HOME_PATH) { grobidHome = new File(pGROBID_HOME_PATH); // exception if prop file does not exist if (!grobidHome.exists()) { - throw new GrobidPropertyException("Could not read GROBID_HOME, the directory '" + pGROBID_HOME_PATH + "' does not exist."); + throw new GrobidPropertyException( + "Could not read GROBID_HOME, the directory '" + pGROBID_HOME_PATH + "' does not exist."); } try { grobidHome = grobidHome.getCanonicalFile(); } catch (IOException e) { throw new GrobidPropertyException("Cannot set grobid home path to the given one '" + pGROBID_HOME_PATH - + "', because it does not exist."); + + "', because it does not exist."); } } @@ -216,14 +223,16 @@ public static void setGrobidConfigPath(final String pGrobidConfigPath) { File grobidConfigPath = new File(pGrobidConfigPath); // exception if config file does not exist if (!grobidConfigPath.exists()) { - throw new GrobidPropertyException("Cannot read GROBID yaml config file, the file '" + pGrobidConfigPath + "' does not exist."); + throw new GrobidPropertyException( + "Cannot read GROBID yaml config file, the file '" + pGrobidConfigPath + "' does not exist."); } try { GROBID_CONFIG_PATH = grobidConfigPath.getCanonicalFile(); } catch (IOException e) { - throw new GrobidPropertyException("Cannot set grobid yaml config file path to the given one '" + pGrobidConfigPath - + "', because it does not exist."); + throw new GrobidPropertyException( + "Cannot set grobid yaml config file path to the given one '" + pGrobidConfigPath + + "', because it does not exist."); } } @@ -247,14 +256,18 @@ public GrobidProperties() { mapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES); grobidConfig = mapper.readValue(GROBID_CONFIG_PATH, GrobidConfig.class); } catch (IOException exp) { - throw new GrobidPropertyException("Cannot open GROBID config yaml file at location '" + GROBID_CONFIG_PATH.getAbsolutePath() - + "'", exp); + throw new GrobidPropertyException( + "Cannot open GROBID config yaml file at location '" + GROBID_CONFIG_PATH.getAbsolutePath() + + "'", + exp); } catch (Exception exp) { - throw new GrobidPropertyException("Cannot open GROBID config yaml file " + getGrobidConfigPath().getAbsolutePath(), exp); + throw new GrobidPropertyException( + "Cannot open GROBID config yaml file " + getGrobidConfigPath().getAbsolutePath(), exp); } - //Map configParametersViaEnvironment = getEnvironmentVariableOverrides(System.getenv()); - //this.setEnvironmentConfigParameter(configParametersViaEnvironment); + // Map configParametersViaEnvironment = + // getEnvironmentVariableOverrides(System.getenv()); + // this.setEnvironmentConfigParameter(configParametersViaEnvironment); initializeTmpPath(); // TBD: tmp to be created @@ -266,7 +279,7 @@ public GrobidProperties() { * Create a map between model names and associated parameters */ private static void createModelMap() { - for(ModelParameters modelParameter : grobidConfig.grobid.models) { + for (ModelParameters modelParameter : grobidConfig.grobid.models) { if (modelMap == null) modelMap = new TreeMap<>(); modelMap.put(modelParameter.name, modelParameter); @@ -295,7 +308,8 @@ private void initializeTmpPath() { } /** - * Return the distinct values of all the engines that are specified in the the model map + * Return the distinct values of all the engines that are specified in the the + * model map */ public static Set getDistinctModels() { Set distinctModels = new HashSet<>(); @@ -313,6 +327,16 @@ public static Set getDistinctModels() { return distinctModels; } + /** + * Return all model names from the configuration + */ + public static Set getModelNames() { + if (modelMap == null) { + return Collections.emptySet(); + } + return modelMap.keySet(); + } + /** * Returns the current version of GROBID * @@ -391,7 +415,8 @@ public static File getNativeLibraryPath() { } /** - * Returns the installation path of DeLFT if set, null otherwise. It is required for using + * Returns the installation path of DeLFT if set, null otherwise. It is required + * for using * a Deep Learning sequence labelling engine. * * @return path to the folder that contains the local install of DeLFT @@ -470,7 +495,8 @@ public static void setCrossrefMailto(final String mailto) { * @return string of the email parameter to be used for requesting crossref */ public static String getCrossrefMailto() { - if (grobidConfig.grobid.consolidation.crossref.mailto == null || grobidConfig.grobid.consolidation.crossref.mailto.trim().length() == 0) + if (grobidConfig.grobid.consolidation.crossref.mailto == null + || grobidConfig.grobid.consolidation.crossref.mailto.trim().length() == 0) return null; else return grobidConfig.grobid.consolidation.crossref.mailto; @@ -478,8 +504,10 @@ public static String getCrossrefMailto() { /** * Set the Crossref Metadata Plus authorization token to be used for Crossref - * requests for the subscribers of this service. This token will ensure that said - * requests get directed to a pool of machines that are reserved for "Plus" SLA users. + * requests for the subscribers of this service. This token will ensure that + * said + * requests get directed to a pool of machines that are reserved for "Plus" SLA + * users. * * @param token authorization token to be used for requesting crossref */ @@ -489,13 +517,16 @@ public static void setCrossrefToken(final String token) { /** * Get the Crossref Metadata Plus authorization token to be used for Crossref - * requests for the subscribers of this service. This token will ensure that said - * requests get directed to a pool of machines that are reserved for "Plus" SLA users. + * requests for the subscribers of this service. This token will ensure that + * said + * requests get directed to a pool of machines that are reserved for "Plus" SLA + * users. * * @return authorization token to be used for requesting crossref */ public static String getCrossrefToken() { - if (grobidConfig.grobid.consolidation.crossref.token == null || grobidConfig.grobid.consolidation.crossref.token.trim().length() == 0) + if (grobidConfig.grobid.consolidation.crossref.token == null + || grobidConfig.grobid.consolidation.crossref.token.trim().length() == 0) return null; else return grobidConfig.grobid.consolidation.crossref.token; @@ -508,8 +539,8 @@ public static String getCrossrefToken() { */ public static void setProxyPort(int port) { grobidConfig.grobid.proxy.port = port; - System.setProperty("http.proxyPort", ""+port); - System.setProperty("https.proxyPort", ""+port); + System.setProperty("http.proxyPort", "" + port); + System.setProperty("https.proxyPort", "" + port); } public static Integer getPdfaltoMemoryLimitMb() { @@ -524,16 +555,20 @@ public static Integer getPdfaltoTimeoutMs() { return grobidConfig.grobid.pdf.pdfalto.timeoutSec * 1000; } - /*public static Integer getNBThreads() { - Integer nbThreadsConfig = Integer.valueOf(grobidConfig.grobid.wapiti.nbThreads); - if (nbThreadsConfig.intValue() == 0) { - return Integer.valueOf(Runtime.getRuntime().availableProcessors()); - } - return nbThreadsConfig; - }*/ + /* + * public static Integer getNBThreads() { + * Integer nbThreadsConfig = + * Integer.valueOf(grobidConfig.grobid.wapiti.nbThreads); + * if (nbThreadsConfig.intValue() == 0) { + * return Integer.valueOf(Runtime.getRuntime().availableProcessors()); + * } + * return nbThreadsConfig; + * } + */ /** - * Returns the number of threads to be used when training with CRF Wapiti, given in the grobid config file. + * Returns the number of threads to be used when training with CRF Wapiti, given + * in the grobid config file. * * @return number of threads */ @@ -556,13 +591,16 @@ public static Integer getPdfTokensMax() { } /** - * Sets the number of threads for training a Wapiti model, given in the grobid config file. + * Sets the number of threads for training a Wapiti model, given in the grobid + * config file. * * @param nbThreads umber of threads */ - /*public static void setNBThreads(int nbThreads) { - grobidConfig.grobid.wapiti.nbThreads = nbThreads; - }*/ + /* + * public static void setNBThreads(int nbThreads) { + * grobidConfig.grobid.wapiti.nbThreads = nbThreads; + * } + */ public static void setWapitiNbThreads(int nbThreads) { grobidConfig.grobid.wapiti.nbThreads = nbThreads; } @@ -578,9 +616,11 @@ public static String getLanguageDetectorFactory() { /** * Sets if a language id shall be used, given in the grobid-property file. */ - /*public static void setUseLanguageId(final String useLanguageId) { - setPropertyValue(GrobidPropertyKeys.PROP_USE_LANG_ID, useLanguageId); - }*/ + /* + * public static void setUseLanguageId(final String useLanguageId) { + * setPropertyValue(GrobidPropertyKeys.PROP_USE_LANG_ID, useLanguageId); + * } + */ public static String getSentenceDetectorFactory() { String factoryClassName = grobidConfig.grobid.sentenceDetectorFactory; @@ -599,8 +639,8 @@ public static void loadPdfaltoPath() { pathToPdfalto = new File(grobidHome.getPath(), pathName); if (!pathToPdfalto.exists()) { throw new GrobidPropertyException( - "Path to pdfalto doesn't exists. " + - "Please set the path to pdfalto in the config file"); + "Path to pdfalto doesn't exists. " + + "Please set the path to pdfalto in the config file"); } pathToPdfalto = new File(pathToPdfalto, Utilities.getOsNameAndArch()); @@ -622,11 +662,11 @@ public static ModelParameters getGrobidModelParameters(final String modelName) { // if we have a flavor of the model, we can fall back to the configuration // of the parent model String fallBackModelName = modelName; - while(param == null) { + while (param == null) { LOGGER.debug("No configuration parameter defined for model " + modelName); int ind = fallBackModelName.lastIndexOf("-"); if (ind != -1) { - fallBackModelName = modelName.substring(0,ind); + fallBackModelName = modelName.substring(0, ind); } else { return null; } @@ -655,21 +695,40 @@ public static GrobidCRFEngine getGrobidEngine(final GrobidModel model) { } public static File getModelPath(final GrobidModel model) { - if (modelMap.get(model.getModelName()) == null) { - // model is either: - // - a flavor without config, but that should fallback to the parent model config - // if no specific config exists. If it is the case, the model path is infered - // from the flavor model name - // - a normal model not specified in the config, so returning null - - if (getGrobidModelParameters(model.getModelName()) == null) { - return null; - } + if (getGrobidModelParameters(model.getModelName()) == null) { + return null; + } + + GrobidCRFEngine engine = getGrobidEngine(model); + if (engine == null) { + return null; + } + + switch (engine) { + case ONNX: + String onnxArch = getOnnxArchitecture(model); + if (onnxArch == null) + return null; + String onnxDirName = model.getModelName() + "-" + onnxArch + ".onnx"; + return new File(getModelPath(), onnxDirName); + + case DELFT: + String delftArch = getDelftArchitecture(model); + String delftDirName = model.getModelName(); + if (delftArch != null) { + delftDirName += "-" + delftArch; + } + if (useELMo(model.getModelName()) && !model.getModelName().toLowerCase().contains("bert")) { + delftDirName += "-with_ELMo"; + } + return new File(getModelPath(), delftDirName); + + default: // WAPITI, CRFPP, DUMMY + String extension = engine.getExt(); + return new File(getGrobidHome(), FOLDER_NAME_MODELS + File.separator + + model.getFolderName() + File.separator + + FILE_NAME_MODEL + "." + extension); } - String extension = getGrobidEngine(model).getExt(); - return new File(getGrobidHome(), FOLDER_NAME_MODELS + File.separator - + model.getFolderName() + File.separator - + FILE_NAME_MODEL + "." + extension); } public static File getModelPath() { @@ -682,10 +741,10 @@ public static File getTemplatePath(final File resourcesDir, final GrobidModel mo return null; File theFile = new File(resourcesDir, "dataset/" + model.getFolderName() - + "/crfpp-templates/" + model.getTemplateName()); + + "/crfpp-templates/" + model.getTemplateName()); if (!theFile.exists()) { theFile = new File("resources/dataset/" + model.getFolderName() - + "/crfpp-templates/" + model.getTemplateName()); + + "/crfpp-templates/" + model.getTemplateName()); } return theFile; } @@ -753,6 +812,7 @@ public static void setConsolidationService(String service) { /** * Get the Crossref timeout in seconds for consolidation service requests. + * * @return timeout in seconds */ public static int getCrossrefConsolidationTimeout() { @@ -765,6 +825,7 @@ public static int getCrossrefConsolidationTimeout() { /** * Get the Glutton timeout in seconds for consolidation service requests. + * * @return timeout in seconds */ public static int getGluttonConsolidationTimeout() { @@ -779,7 +840,7 @@ public static int getGluttonConsolidationTimeout() { * Returns if the execution context is stand alone or server. * * @return the context of execution. Return false if the property value is - * null or empty. + * null or empty. */ public static boolean isContextExecutionServer() { return contextExecutionServer; @@ -883,8 +944,9 @@ public static String getDelftTranformer(final String modelName) { } /** - * Return -1 if not set in the configuration and the default DeLFT value will be used in this case. - */ + * Return -1 if not set in the configuration and the default DeLFT value will be + * used in this case. + */ public static int getDelftTrainingMaxSequenceLength(final String modelName) { ModelParameters param = getGrobidModelParameters(modelName); if (param == null) { @@ -906,8 +968,9 @@ public static int getDelftTrainingMaxSequenceLength(final String modelName) { } /** - * Return -1 if not set in the configuration and the default DeLFT value will be used in this case. - */ + * Return -1 if not set in the configuration and the default DeLFT value will be + * used in this case. + */ public static int getDelftRuntimeMaxSequenceLength(final String modelName) { ModelParameters param = getGrobidModelParameters(modelName); if (param == null) { @@ -929,8 +992,9 @@ public static int getDelftRuntimeMaxSequenceLength(final String modelName) { } /** - * Return -1 if not set in the configuration and the default DeLFT value will be used in this case. - */ + * Return -1 if not set in the configuration and the default DeLFT value will be + * used in this case. + */ public static int getDelftTrainingBatchSize(final String modelName) { ModelParameters param = getGrobidModelParameters(modelName); if (param == null) { @@ -952,8 +1016,9 @@ public static int getDelftTrainingBatchSize(final String modelName) { } /** - * Return -1 if not set in the configuration and the default DeLFT value will be used in this case. - */ + * Return -1 if not set in the configuration and the default DeLFT value will be + * used in this case. + */ public static int getDelftRuntimeBatchSize(final String modelName) { ModelParameters param = getGrobidModelParameters(modelName); if (param == null) { @@ -976,10 +1041,68 @@ public static int getDelftRuntimeBatchSize(final String modelName) { public static String getDelftArchitecture(final GrobidModel model) { return getDelftArchitecture(model.getModelName()); - } + } - /*protected static Map getEnvironmentVariableOverrides(Map environmentVariablesMap) { - EnvironmentVariableProperties envParameters = new EnvironmentVariableProperties(environmentVariablesMap, "(grobid__).+"); - return envParameters.getConfigParameters(); - }*/ + public static String getOnnxArchitecture(final String modelName) { + ModelParameters param = getGrobidModelParameters(modelName); + if (param == null) { + LOGGER.debug("No configuration parameter defined for model " + modelName); + return null; + } + GrobidConfig.OnnxModelParameters onnxParam = param.onnx; + if (onnxParam != null && onnxParam.architecture != null) { + return onnxParam.architecture; + } + // Fallback to DeLFT architecture if ONNX not specified + return getDelftArchitecture(modelName); + } + + public static String getOnnxArchitecture(final GrobidModel model) { + return getOnnxArchitecture(model.getModelName()); + } + + /** + * Return -1 if not set in the configuration. + * When -1 is returned, the value should be read from the model's config.json. + */ + public static int getOnnxRuntimeMaxSequenceLength(final String modelName) { + ModelParameters param = getGrobidModelParameters(modelName); + if (param == null) { + LOGGER.debug("No configuration parameter defined for model " + modelName); + return -1; + } + GrobidConfig.OnnxModelParameters onnxParam = param.onnx; + if (onnxParam == null) { + LOGGER.debug("No configuration parameter defined for ONNX engine for model " + modelName); + return -1; + } + return onnxParam.max_sequence_length; + } + + /** + * Return -1 if not set in the configuration. + */ + public static int getOnnxRuntimeBatchSize(final String modelName) { + ModelParameters param = getGrobidModelParameters(modelName); + if (param == null) { + LOGGER.debug("No configuration parameter defined for model " + modelName); + return -1; + } + GrobidConfig.OnnxModelParameters onnxParam = param.onnx; + if (onnxParam == null) { + LOGGER.debug("No configuration parameter defined for ONNX engine for model " + modelName); + return -1; + } + return onnxParam.batch_size; + } + + /* + * protected static Map + * getEnvironmentVariableOverrides(Map environmentVariablesMap) + * { + * EnvironmentVariableProperties envParameters = new + * EnvironmentVariableProperties(environmentVariablesMap, "(grobid__).+"); + * return envParameters.getConfigParameters(); + * } + */ } diff --git a/grobid-core/src/main/java/org/grobid/core/utilities/TestEngineUtils.java b/grobid-core/src/main/java/org/grobid/core/utilities/TestEngineUtils.java new file mode 100644 index 0000000000..a28503a8ea --- /dev/null +++ b/grobid-core/src/main/java/org/grobid/core/utilities/TestEngineUtils.java @@ -0,0 +1,64 @@ +package org.grobid.core.utilities; + +import org.grobid.core.engines.tagging.GrobidCRFEngine; +import org.grobid.core.factory.AbstractEngineFactory; + +/** + * Test utilities to make Grobid tests independent of the active grobid.yaml. + * + * A number of unit/integration tests assume Wapiti-style CRF models. + * When grobid.yaml is configured to use DeLFT or ONNX for some models + * (e.g. header, reference-segmenter, citation), these tests can fail. + */ +public class TestEngineUtils { + + private static volatile boolean wapitiForced = false; + + private TestEngineUtils() { + // utility class + } + + /** + * Initialize Grobid and force all configured model engines to Wapiti. + * + * Should be called in {@code @BeforeClass} before any Engine/Parser is created. + */ + public static void initGrobidForceWapiti() { + // Ensure config/modelMap is loaded + GrobidProperties.getInstance(); + + if (!wapitiForced) { + synchronized (TestEngineUtils.class) { + if (!wapitiForced) { + forceAllModelsToWapiti(); + wapitiForced = true; + } + } + } + + // Continue with the normal initialization path + AbstractEngineFactory.init(); + } + + private static void forceAllModelsToWapiti() { + // Iterate over all model names from the configuration (not just enum values) + // to ensure all models including citation, header, reference-segmenter etc. are forced to wapiti + for (String modelName : GrobidProperties.getModelNames()) { + GrobidConfig.ModelParameters current = GrobidProperties.getGrobidModelParameters(modelName); + if (current == null) { + continue; + } + + // Overwrite engine selection only + GrobidConfig.ModelParameters override = new GrobidConfig.ModelParameters(); + override.name = current.name; + override.engine = GrobidCRFEngine.WAPITI.name().toLowerCase(); + override.wapiti = current.wapiti; + override.delft = current.delft; + override.onnx = current.onnx; + + GrobidProperties.addModel(override); + } + } +} + diff --git a/grobid-core/src/main/resources/large_sequence.txt b/grobid-core/src/main/resources/large_sequence.txt new file mode 100644 index 0000000000..83dbdf4e10 --- /dev/null +++ b/grobid-core/src/main/resources/large_sequence.txt @@ -0,0 +1,6747 @@ +12 12 1 12 12 12 2 12 12 12 LINESTART ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKSTART 10 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 4 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +9 9 9 9 9 9 9 9 9 9 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Jacob jacob J Ja Jac Jaco b ob cob acob LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Devlin devlin D De Dev Devl n in lin vlin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 9 0 +Ming ming M Mi Min Ming g ng ing Ming LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 9 BLOCKIN 9 0 +Wei wei W We Wei Wei i ei Wei Wei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +Chang chang C Ch Cha Chan g ng ang hang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Kenton kenton K Ke Ken Kent n on ton nton LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Lee lee L Le Lee Lee e ee Lee Lee LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 9 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Kristina kristina K Kr Kri Kris a na ina tina LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +Toutanova toutanova T To Tou Tout a va ova nova LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 5 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 8 BLOCKSTART 7 0 +10 10 1 10 10 10 0 10 10 10 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 7 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 8 BLOCKIN 7 0 +Aakanksha aakanksha A Aa Aak Aaka a ha sha ksha LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 7 0 +Chowdhery chowdhery C Ch Cho Chow y ry ery hery LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 8 BLOCKIN 7 0 +Sharan sharan S Sh Sha Shar n an ran aran LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +Narang narang N Na Nar Nara g ng ang rang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 8 BLOCKIN 6 0 +Dai dai D Da Dai Dai i ai Dai Dai LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 0 8 BLOCKIN 6 0 +Thanumalayan thanumalayan T Th Tha Than n an yan ayan LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 6 0 +Sankaranarayana sankaranarayana S Sa San Sank a na ana yana LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 6 0 +Pillai pillai P Pi Pil Pill i ai lai llai LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 6 0 +Marie marie M Ma Mar Mari e ie rie arie LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 6 0 +Pellat pellat P Pe Pel Pell t at lat llat LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 6 0 +Aitor aitor A Ai Ait Aito r or tor itor LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 6 0 +Lewkowycz lewkowycz L Le Lew Lewk z cz ycz wycz LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 8 BLOCKIN 6 0 +Erica erica E Er Eri Eric a ca ica rica LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 6 0 +Moreira moreira M Mo Mor More a ra ira eira LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 8 BLOCKIN 6 0 +Re re R Re Re Re e Re Re Re LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 6 0 +- - - - - - - - - - LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 10 8 BLOCKIN 6 0 +won won w wo won won n on won won LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 6 0 +Child child C Ch Chi Chil d ld ild hild LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 6 0 +Oleksandr oleksandr O Ol Ole Olek r dr ndr andr LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 6 0 +Polozov polozov P Po Pol Polo v ov zov ozov LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 8 BLOCKIN 6 0 +Katherine katherine K Ka Kat Kath e ne ine rine LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 6 0 +Lee lee L Le Lee Lee e ee Lee Lee LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 8 BLOCKIN 6 0 +Zongwei zongwei Z Zo Zon Zong i ei wei gwei LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 6 0 +Zhou zhou Z Zh Zho Zhou u ou hou Zhou LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 6 0 +Xuezhi xuezhi X Xu Xue Xuez i hi zhi ezhi LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 6 0 +Wang wang W Wa Wan Wang g ng ang Wang LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 8 BLOCKIN 6 0 +Brennan brennan B Br Bre Bren n an nan nnan LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 6 0 +Saeta saeta S Sa Sae Saet a ta eta aeta LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 6 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 8 BLOCKIN 6 0 +Mark mark M Ma Mar Mark k rk ark Mark LINEEND LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 6 0 +Diaz diaz D Di Dia Diaz z az iaz Diaz LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 0 9 BLOCKIN 8 0 +Orhan orhan O Or Orh Orha n an han rhan LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Firat firat F Fi Fir Fira t at rat irat LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Michele michele M Mi Mic Mich e le ele hele LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +Catasta catasta C Ca Cat Cata a ta sta asta LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 8 0 +Jason jason J Ja Jas Jaso n on son ason LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Wei wei W We Wei Wei i ei Wei Wei LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +Kathy kathy K Ka Kat Kath y hy thy athy LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Meier meier M Me Mei Meie r er ier eier LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 7 9 BLOCKIN 8 0 +Hellstern hellstern H He Hel Hell n rn ern tern LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 8 0 +Douglas douglas D Do Dou Doug s as las glas LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +Eck eck E Ec Eck Eck k ck Eck Eck LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 9 BLOCKIN 8 0 +Jeff jeff J Je Jef Jeff f ff eff Jeff LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +Dean dean D De Dea Dean n an ean Dean LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +, , , , , , , , , , LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 8 0 +Slav slav S Sl Sla Slav v av lav Slav LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 5 0 +Petrov petrov P Pe Pet Petr v ov rov trov LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 5 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 5 0 +Noah noah N No Noa Noah h ah oah Noah LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 5 0 +Fiedel fiedel F Fi Fie Fied l el del edel LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 5 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 3 8 BLOCKIN 5 0 +Palm palm P Pa Pal Palm m lm alm Palm LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 5 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 4 8 BLOCKIN 5 0 +Scaling scaling S Sc Sca Scal g ng ing ling LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 5 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 5 0 +modeling modeling m mo mod mode g ng ing ling LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 5 0 +with with w wi wit with h th ith with LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 5 0 +pathways pathways p pa pat path s ys ays ways LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 8 BLOCKIN 5 0 +2022 2022 2 20 202 2022 2 22 022 2022 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 8 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +11 11 1 11 11 11 1 11 11 11 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Hugo hugo H Hu Hug Hugo o go ugo Hugo LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Touvron touvron T To Tou Touv n on ron vron LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Thibaut thibaut T Th Thi Thib t ut aut baut LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Lavril lavril L La Lav Lavr l il ril vril LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 8 0 +Gautier gautier G Ga Gau Gaut r er ier tier LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Izacard izacard I Iz Iza Izac d rd ard card LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +Xavier xavier X Xa Xav Xavi r er ier vier LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Martinet martinet M Ma Mar Mart t et net inet LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 8 0 +Marie marie M Ma Mar Mari e ie rie arie LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +- - 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 8 BLOCKIN 7 0 +Tensorflow tensorflow T Te Ten Tens w ow low flow LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 8 BLOCKIN 7 0 +Large large L La Lar Larg e ge rge arge LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 7 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 9 8 BLOCKIN 7 0 +scale scale s sc sca scal e le ale cale LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +machine machine m ma mac mach e ne ine hine LINEEND LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +learning learning l le lea lear g ng ing ning LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 5 0 +on on o on on on n on on on LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +heterogeneous heterogeneous h he het hete s us ous eous LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 5 0 +distributed distributed d di dis dist d ed ted uted LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 5 0 +systems systems s sy sys syst s ms ems tems LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 5 0 +. . . . . . . . . . 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 8 BLOCKIN 5 0 +04467 04467 0 04 044 0446 7 67 467 4467 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 8 BLOCKIN 5 0 +2015 2015 2 20 201 2015 5 15 015 2015 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 8 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +38 38 3 38 38 38 8 38 38 38 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Jacob jacob J Ja Jac Jaco b ob cob acob LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Devlin devlin D De Dev Devl n in lin vlin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 9 0 +Ming ming M Mi Min Ming g ng ing Ming LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 9 BLOCKIN 9 0 +Wei wei W We Wei Wei i ei Wei Wei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Chang chang C Ch Cha Chan g ng ang hang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Kenton kenton K Ke Ken Kent n on ton nton LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Lee lee L Le Lee Lee e ee Lee Lee LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 9 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Kristina kristina K Kr Kri Kris a na ina tina LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +Toutanova toutanova T To Tou Tout a va ova nova LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 9 BLOCKIN 9 0 +Bert bert B Be Ber Bert t rt ert Bert LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +: : : : : : : : : : LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 9 BLOCKIN 9 0 +Pre pre P Pr Pre Pre e re Pre Pre LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 9 9 BLOCKIN 9 0 +training training t tr tra trai g ng ing ning LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +of of o of of of f of of of LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +deep deep d de dee deep p ep eep deep LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +bidirectional bidirectional b bi bid bidi l al nal onal LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 5 0 +transformers transformers t tr tra tran s rs ers mers LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 5 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 5 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 5 0 +understanding understanding u un und unde g ng ing ding LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 6 9 BLOCKIN 5 0 +arXiv arxiv a ar arX arXi v iv Xiv rXiv LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +preprint preprint p pr pre prep t nt int rint LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 5 0 +arXiv arxiv a ar arX arXi v iv Xiv rXiv LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 5 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 9 BLOCKIN 5 0 +1810 1810 1 18 181 1810 0 10 810 1810 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 9 9 BLOCKIN 5 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +39 39 3 39 39 39 9 39 39 39 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Yinhan yinhan Y Yi Yin Yinh n an han nhan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Liu liu L Li Liu Liu u iu Liu Liu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 9 0 +Myle myle M My Myl Myle e le yle Myle LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +Ott ott O Ot Ott Ott t tt Ott Ott LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Naman naman N Na Nam Nama n an man aman LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Goyal goyal G Go Goy Goya l al yal oyal LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 9 0 +Jingfei jingfei J Ji Jin Jing i ei fei gfei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Du du D Du Du Du u Du Du Du LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 9 0 +Mandar mandar M Ma Man Mand r ar dar ndar LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +Joshi joshi J Jo Jos Josh i hi shi oshi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 9 0 +Danqi danqi D Da Dan Danq i qi nqi anqi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +Chen chen C Ch Che Chen n en hen Chen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 9 BLOCKIN 9 0 +Omer omer O Om Ome Omer r er mer Omer LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Levy levy L Le Lev Levy y vy evy Levy LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 9 0 +Mike mike M Mi Mik Mike e ke ike Mike LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Lewis lewis L Le Lew Lewi s is wis ewis LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 0 9 BLOCKIN 4 0 +Luke luke L Lu Luk Luke e ke uke Luke LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 4 0 +Zettlemoyer zettlemoyer Z Ze Zet Zett r er yer oyer LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 4 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 4 0 +Veselin veselin V Ve Ves Vese n in lin elin LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 4 0 +Stoyanov stoyanov S St Sto Stoy v ov nov anov LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 4 0 +. . . . . . . . . . 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 8 BLOCKIN 7 0 +Tensorflow tensorflow T Te Ten Tens w ow low flow LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 8 BLOCKIN 7 0 +Large large L La Lar Larg e ge rge arge LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 7 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 9 8 BLOCKIN 7 0 +scale scale s sc sca scal e le ale cale LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +machine machine m ma mac mach e ne ine hine LINEEND LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +learning learning l le lea lear g ng ing ning LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 5 0 +on on o on on on n on on on LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +heterogeneous heterogeneous h he het hete s us ous eous LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 5 0 +distributed distributed d di dis dist d ed ted uted LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 5 0 +systems systems s sy sys syst s ms ems tems LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 5 0 +. . . . . . . . . . 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 8 BLOCKIN 5 0 +04467 04467 0 04 044 0446 7 67 467 4467 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 8 BLOCKIN 5 0 +2015 2015 2 20 201 2015 5 15 015 2015 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 8 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +38 38 3 38 38 38 8 38 38 38 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Jacob jacob J Ja Jac Jaco b ob cob acob LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Devlin devlin D De Dev Devl n in lin vlin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 9 0 +Ming ming M Mi Min Ming g ng ing Ming LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 9 BLOCKIN 9 0 +Wei wei W We Wei Wei i ei Wei Wei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Chang chang C Ch Cha Chan g ng ang hang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Kenton kenton K Ke Ken Kent n on ton nton LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Lee lee L Le Lee Lee e ee Lee Lee LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 9 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Kristina kristina K Kr Kri Kris a na ina tina LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +Toutanova toutanova T To Tou Tout a va ova nova LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 9 BLOCKIN 9 0 +Bert bert B Be Ber Bert t rt ert Bert LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +: : : : : : : : : : LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 9 BLOCKIN 9 0 +Pre pre P Pr Pre Pre e re Pre Pre LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 9 9 BLOCKIN 9 0 +training training t tr tra trai g ng ing ning LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +of of o of of of f of of of LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +deep deep d de dee deep p ep eep deep LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +bidirectional bidirectional b bi bid bidi l al nal onal LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 5 0 +transformers transformers t tr tra tran s rs ers mers LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 5 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 5 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 5 0 +understanding understanding u un und unde g ng ing ding LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 6 9 BLOCKIN 5 0 +arXiv arxiv a ar arX arXi v iv Xiv rXiv LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +preprint preprint p pr pre prep t nt int rint LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 5 0 +arXiv arxiv a ar arX arXi v iv Xiv rXiv LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 5 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 8 9 BLOCKIN 5 0 +1810 1810 1 18 181 1810 0 10 810 1810 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 9 9 BLOCKIN 5 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +39 39 3 39 39 39 9 39 39 39 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Yinhan yinhan Y Yi Yin Yinh n an han nhan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Liu liu L Li Liu Liu u iu Liu Liu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 9 0 +Myle myle M My Myl Myle e le yle Myle LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +Ott ott O Ot Ott Ott t tt Ott Ott LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Naman naman N Na Nam Nama n an man aman LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Goyal goyal G Go Goy Goya l al yal oyal LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 9 0 +Jingfei jingfei J Ji Jin Jing i ei fei gfei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Du du D Du Du Du u Du Du Du LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 9 0 +Mandar mandar M Ma Man Mand r ar dar ndar LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +Joshi joshi J Jo Jos Josh i hi shi oshi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 9 0 +Danqi danqi D Da Dan Danq i qi nqi anqi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +Chen chen C Ch Che Chen n en hen Chen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 9 BLOCKIN 9 0 +Omer omer O Om Ome Omer r er mer Omer LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Levy levy L Le Lev Levy y vy evy Levy LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 9 0 +Mike mike M Mi Mik Mike e ke ike Mike LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Lewis lewis L Le Lew Lewi s is wis ewis LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 0 9 BLOCKIN 4 0 +Luke luke L Lu Luk Luke e ke uke Luke LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 4 0 +Zettlemoyer zettlemoyer Z Ze Zet Zett r er yer oyer LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 4 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 4 0 +Veselin veselin V Ve Ves Vese n in lin elin LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 4 0 +Stoyanov stoyanov S St Sto Stoy v ov nov anov LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 4 0 +. . . . . . . . . . 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 4 8 BLOCKIN 3 0 +Towards towards T To Tow Towa s ds rds ards LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 3 0 +expert expert e ex exp expe t rt ert pert LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 6 8 BLOCKIN 3 0 +level level l le lev leve l el vel evel LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 3 0 +medical medical m me med medi l al cal ical LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 3 0 +question question q qu que ques n on ion tion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 3 0 +answering answering a an ans answ g ng ing ring LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 3 0 +with with w wi wit with h th ith with LINEEND LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 3 0 +large large l la lar larg e ge rge arge LINESTART LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 1 2 BLOCKIN 2 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 2 BLOCKIN 2 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 2 BLOCKIN 2 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 2 BLOCKIN 2 0 +2023 2023 2 20 202 2023 3 23 023 2023 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 2 BLOCKIN 2 0 +. . . . . . . . . . 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iji uiji LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 8 0 +Zhang zhang Z Zh Zha Zhan g ng ang hang LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 8 0 +Yubin yubin Y Yu Yub Yubi n in bin ubin LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 8 0 +Xia xia X Xi Xia Xia a ia Xia Xia LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 8 BLOCKIN 8 0 +Chaobo chaobo C Ch Cha Chao o bo obo aobo LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 8 0 +Xu xu X Xu Xu Xu u Xu Xu Xu LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 8 0 +Ran ran R Ra Ran Ran n an Ran Ran LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +80 80 8 80 80 80 0 80 80 80 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Hakan hakan H Ha Hak Haka n an kan akan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Inan inan I In Ina Inan n an nan Inan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 8 0 +Kartikeya kartikeya K Ka Kar Kart a ya eya keya LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Upasani upasani U Up Upa Upas i ni ani sani LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 8 0 +Jianfeng jianfeng J Ji Jia Jian g ng eng feng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Chi chi C Ch Chi Chi i hi Chi Chi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +Rashi rashi R Ra Ras Rash i hi shi ashi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Rungta rungta R Ru Run Rung a ta gta ngta LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 8 0 +Krithika krithika K Kr Kri Krit a ka ika hika LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +Iyer iyer I Iy Iye Iyer r er yer Iyer LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 8 0 +Yuning yuning Y Yu Yun Yuni g ng ing ning LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +Mao mao M Ma Mao Mao o ao Mao Mao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 8 0 +Michael michael M Mi Mic Mich l el ael hael LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +Tontchev tontchev T To Ton Tont v ev hev chev LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 7 0 +Qing qing Q Qi Qin Qing g ng ing Qing LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 7 0 +Hu hu H Hu Hu Hu u Hu Hu Hu LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 8 BLOCKIN 7 0 +Brian brian B Br Bri Bria n an ian rian LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +Fuller fuller F Fu Ful Full r er ler ller LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 7 0 +Davide davide D Da Dav Davi e de ide vide LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 7 0 +Testuggine testuggine T Te Tes Test e ne ine gine LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +Madian madian M Ma Mad Madi n an ian dian LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 7 0 +Khabsa khabsa K Kh Kha Khab a sa bsa absa LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 8 BLOCKIN 7 0 +Llama llama L Ll Lla Llam a ma ama lama LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 7 0 +guard guard g gu gua guar d rd ard uard LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 10 8 BLOCKIN 7 0 +Llm llm L Ll Llm Llm m lm Llm Llm LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +- - - - - - - - - - LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 10 8 BLOCKIN 7 0 +based based b ba bas base d ed sed ased LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 4 0 +input input i in inp inpu t ut put nput LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 6 BLOCKIN 4 0 +output output o ou out outp t ut put tput LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 6 BLOCKIN 4 0 +safeguard safeguard s sa saf safe d rd ard uard LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 4 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 6 BLOCKIN 4 0 +human human h hu hum huma n an man uman LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 6 6 BLOCKIN 4 0 +ai ai a ai ai ai i ai ai ai LINEIN LINEINDENT NOCAPS NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 6 BLOCKIN 4 0 +conversations conversations c co con conv s ns ons ions LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 4 0 +2023 2023 2 20 202 2023 3 23 023 2023 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 4 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 4 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +81 81 8 81 81 81 1 81 81 81 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Wenjun wenjun W We Wen Wenj n un jun njun LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Zeng zeng Z Ze Zen Zeng g ng eng Zeng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 8 0 +Yuchi yuchi Y Yu Yuc Yuch i hi chi uchi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Liu liu L Li Liu Liu u iu Liu Liu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 8 0 +Ryan ryan R Ry Rya Ryan n an yan Ryan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +Mullins mullins M Mu Mul Mull s ns ins lins LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 8 0 +Ludovic ludovic L Lu Lud Ludo c ic vic ovic LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +Peran peran P Pe Per Pera n an ran eran LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 8 0 +Joe joe J Jo Joe Joe e oe Joe Joe LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +Fernandez fernandez F Fe Fer Fern z ez dez ndez LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 8 0 +Hamza hamza H Ha Ham Hamz a za mza amza LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +Harkous harkous H Ha Har Hark s us ous kous LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 8 0 +Karthik karthik K Ka Kar Kart k ik hik thik LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +Narasimhan narasimhan N Na Nar Nara n an han mhan LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 5 0 +Drew drew D Dr Dre Drew w ew rew Drew LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +Proud proud P Pr Pro Prou d ud oud roud LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 8 BLOCKIN 5 0 +Piyush piyush P Pi Piy Piyu h sh ush yush LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 5 0 +Kumar kumar K Ku Kum Kuma r ar mar umar LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 5 0 +Bhaktipriya bhaktipriya B Bh Bha Bhak a ya iya riya LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 5 0 +Radharapu radharapu R Ra Rad Radh u pu apu rapu LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 8 BLOCKIN 5 0 +Olivia olivia O Ol Oli Oliv a ia via ivia LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 5 0 +Sturman sturman S St Stu Stur n an man rman LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 8 BLOCKIN 5 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +Oscar oscar O Os Osc Osca r ar car scar LINEEND LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +Wahltinez wahltinez W Wa Wah Wahl z ez nez inez LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 7 BLOCKIN 4 0 +. . . . . . . . . . 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 6 8 BLOCKIN 8 0 +Truong truong T Tr Tru Truo g ng ong uong LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 8 BLOCKIN 8 0 +Simran simran S Si Sim Simr n an ran mran LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 8 0 +Arora arora A Ar Aro Aror a ra ora rora LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 8 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 8 BLOCKIN 8 0 +Mantas mantas M Ma Man Mant s as tas ntas LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 8 0 +Mazeika mazeika M Ma Maz Maze a ka ika eika LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 8 0 +, , , , , , , , , , LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 8 BLOCKIN 8 0 +Dan dan D Da Dan Dan n an Dan Dan LINESTART LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 7 0 +Hendrycks hendrycks H He Hen Hend s ks cks ycks LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 7 0 +Zinan zinan Z Zi Zin Zina n an nan inan LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 7 0 +Lin lin L Li Lin Lin n in Lin Lin LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 8 BLOCKIN 7 0 +Yu yu Y Yu Yu Yu u Yu Yu Yu LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +Cheng cheng C Ch Che Chen g ng eng heng LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 7 0 +Sanmi sanmi S Sa San Sanm i mi nmi anmi LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 7 0 +Koyejo koyejo K Ko Koy Koye o jo ejo yejo LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 7 0 +Dawn dawn D Da Daw Dawn n wn awn Dawn LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +Song song S So Son Song g ng ong Song LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 8 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +Bo bo B Bo Bo Bo o Bo Bo Bo LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +Li li L Li Li Li i Li Li Li LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 7 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 8 BLOCKIN 7 0 +Decodingtrust decodingtrust D De Dec Deco t st ust rust LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 10 8 BLOCKIN 7 0 +A a A A A A A A A A LINEEND LINEINDENT ALLCAP NODIGIT 1 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +comprehensive comprehensive c co com comp e ve ive sive LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 2 0 +assessment assessment a as ass asse t nt ent ment LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 2 0 +of of o of of of f of of of LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 2 0 +trustworthiness trustworthiness t tr tru trus s ss ess ness LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 2 0 +in in i in in in n in in in LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 7 6 BLOCKIN 2 0 +gpt gpt g gp gpt gpt t pt gpt gpt LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 6 BLOCKIN 2 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 2 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 2 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 2 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +80 80 8 80 80 80 0 80 80 80 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Hakan hakan H Ha Hak Haka n an kan akan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Inan inan I In Ina Inan n an nan Inan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 8 0 +Kartikeya kartikeya K Ka Kar Kart a ya eya keya LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Upasani upasani U Up Upa Upas i ni ani sani LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 8 0 +Jianfeng jianfeng J Ji Jia Jian g ng eng feng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Chi chi C Ch Chi Chi i hi Chi Chi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +Rashi rashi R Ra Ras Rash i hi shi ashi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Rungta rungta R Ru Run Rung a ta gta ngta LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 8 0 +Krithika krithika K Kr Kri Krit a ka ika hika LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +Iyer iyer I Iy Iye Iyer r er yer Iyer LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 8 0 +Yuning yuning Y Yu Yun Yuni g ng ing ning LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +Mao mao M Ma Mao Mao o ao Mao Mao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 8 0 +Michael michael M Mi Mic Mich l el ael hael LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +Tontchev tontchev T To Ton Tont v ev hev chev LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 7 0 +Qing qing Q Qi Qin Qing g ng ing Qing LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 7 0 +Hu hu H Hu Hu Hu u Hu Hu Hu LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 8 BLOCKIN 7 0 +Brian brian B Br Bri Bria n an ian rian LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +Fuller fuller F Fu Ful Full r er ler ller LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 7 0 +Davide davide D Da Dav Davi e de ide vide LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 7 0 +Testuggine testuggine T Te Tes Test e ne ine gine LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 7 0 +Madian madian M Ma Mad Madi n an ian dian LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 7 0 +Khabsa khabsa K Kh Kha Khab a sa bsa absa LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 7 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 8 BLOCKIN 7 0 +Llama llama L Ll Lla Llam a ma ama lama LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 7 0 +guard guard g gu gua guar d rd ard uard LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 10 8 BLOCKIN 7 0 +Llm llm L Ll Llm Llm m lm Llm Llm LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 7 0 +- - - - - - - - - - LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 10 8 BLOCKIN 7 0 +based based b ba bas base d ed sed ased LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 4 0 +input input i in inp inpu t ut put nput LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 6 BLOCKIN 4 0 +output output o ou out outp t ut put tput LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 6 BLOCKIN 4 0 +safeguard safeguard s sa saf safe d rd ard uard LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 4 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 6 BLOCKIN 4 0 +human human h hu hum huma n an man uman LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 6 6 BLOCKIN 4 0 +ai ai a ai ai ai i ai ai ai LINEIN LINEINDENT NOCAPS NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 6 BLOCKIN 4 0 +conversations conversations c co con conv s ns ons ions LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 4 0 +2023 2023 2 20 202 2023 3 23 023 2023 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 4 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 1 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 7 0 +92 92 9 92 92 92 2 92 92 92 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 7 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 7 0 +Mojtaba mojtaba M Mo Moj Mojt a ba aba taba LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 7 0 +Valipour valipour V Va Val Vali r ur our pour LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 7 0 +Mehdi mehdi M Me Meh Mehd i di hdi ehdi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 7 0 +Rezagholizadeh rezagholizadeh R Re Rez Reza h eh deh adeh LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 7 0 +Ivan ivan I Iv Iva Ivan n an van Ivan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 7 0 +Kobyzev kobyzev K Ko Kob Koby v ev zev yzev LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 7 0 +Ali ali A Al Ali Ali i li Ali Ali LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 7 0 +Ghodsi ghodsi G Gh Gho Ghod i si dsi odsi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 7 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 9 BLOCKIN 7 0 +Dylora dylora D Dy Dyl Dylo a ra ora lora LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 7 0 +: : : : : : : : : : LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 9 9 BLOCKIN 7 0 +Parameter parameter P Pa Par Para r er ter eter LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 7 0 +efficient efficient e ef eff effi t nt ent ient LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 5 0 +tuning tuning t tu tun tuni g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 5 0 +of of o of of of f of of of LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 5 0 +pre pre p pr pre pre e re pre pre LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 5 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 8 BLOCKIN 5 0 +trained trained t tr tra trai d ed ned ined LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 5 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 5 0 +using using u us usi usin g ng ing sing LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 5 0 +dynamic dynamic d dy dyn dyna c ic mic amic LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 5 0 +search search s se sea sear h ch rch arch LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 5 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 7 8 BLOCKIN 5 0 +free free f fr fre free e ee ree free LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 5 0 +low low l lo low low w ow low low LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 5 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 8 8 BLOCKIN 5 0 +rank rank r ra ran rank k nk ank rank LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 5 0 +adaptation adaptation a ad ada adap n on ion tion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 8 BLOCKIN 5 0 +2023 2023 2 20 202 2023 3 23 023 2023 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 8 BLOCKIN 5 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 8 BLOCKEND 5 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 10 0 +93 93 9 93 93 93 3 93 93 93 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 10 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 10 0 +Longteng longteng L Lo Lon Long g ng eng teng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 10 0 +Zhang zhang Z Zh Zha Zhan g ng ang hang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 10 0 +Lin lin L Li Lin Lin n in Lin Lin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 10 0 +Zhang zhang Z Zh Zha Zhan g ng ang hang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 10 0 +Shaohuai shaohuai S Sh Sha Shao i ai uai huai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 10 0 +Shi shi S Sh Shi Shi i hi Shi Shi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 10 0 +Xiaowen xiaowen X Xi Xia Xiao n en wen owen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 10 0 +Chu chu C Ch Chu Chu u hu Chu Chu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 10 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 10 0 +Bo bo B Bo Bo Bo o Bo Bo Bo LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 10 0 +Li li L Li Li Li i Li Li Li LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 10 0 +. . . . . . . . . . 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LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 4 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +94 94 9 94 94 94 4 94 94 94 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Qiong qiong Q Qi Qio Qion g ng ong iong LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Wu wu W Wu Wu Wu u Wu Wu Wu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 8 0 +Weihao weihao W We Wei Weih o ao hao ihao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Ye ye Y Ye Ye Ye e Ye Ye Ye LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Yiyi yiyi Y Yi Yiy Yiyi i yi iyi Yiyi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +Zhou zhou Z Zh Zho Zhou u ou hou Zhou LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 8 0 +Xiaoshuai xiaoshuai X Xi Xia Xiao i ai uai huai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +Sun sun S Su Sun Sun n un Sun Sun LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Rongrong rongrong R Ro Ron Rong g ng ong rong LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +Ji ji J Ji Ji Ji i Ji Ji Ji LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 9 BLOCKIN 8 0 +Not not N No Not Not t ot Not Not LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +all all a al all all l ll all all LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +attention attention a at att atte n on ion tion LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +is is i is is is s is is is LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +needed needed n ne nee need d ed ded eded LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +: : : : : : : : : : LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 10 9 BLOCKIN 8 0 +Parameter parameter P Pa Par Para r er ter eter LINESTART LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 3 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 3 0 +computation computation c co com comp n on ion tion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 3 0 +efficient efficient e ef eff effi t nt ent ient LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 3 0 +transfer transfer t tr tra tran r er fer sfer LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 3 0 +learning learning l le lea lear g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 3 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 3 0 +multi multi m mu mul mult i ti lti ulti LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 7 9 BLOCKIN 3 0 +modal modal m mo mod moda l al dal odal LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 3 0 +large large l la lar larg e ge rge arge LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 3 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 3 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 3 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 3 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 9 BLOCKIN 3 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKEND 3 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 8 BLOCKSTART 10 0 +95 95 9 95 95 95 5 95 95 95 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 10 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 8 BLOCKIN 10 0 +Shibo shibo S Sh Shi Shib o bo ibo hibo LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 10 0 +Jie jie J Ji Jie Jie e ie Jie Jie LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 8 BLOCKIN 10 0 +Yehui yehui Y Ye Yeh Yehu i ui hui ehui LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 10 0 +Tang tang T Ta Tan Tang g ng ang Tang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 8 BLOCKIN 10 0 +Ning ning N Ni Nin Ning g ng ing Ning LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 10 0 +Ding ding D Di Din Ding g ng ing Ding LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 8 BLOCKIN 10 0 +Zhi zhi Z Zh Zhi Zhi i hi Zhi Zhi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 10 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 5 8 BLOCKIN 10 0 +Hong hong H Ho Hon Hong g ng ong Hong LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 10 0 +Deng deng D De Den Deng g ng eng Deng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 8 BLOCKIN 10 0 +Kai kai K Ka Kai Kai i ai Kai Kai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 10 0 +Han han H Ha Han Han n an Han Han LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 10 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 8 BLOCKIN 10 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 10 0 +Yunhe yunhe Y Yu Yun Yunh e he nhe unhe LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 10 0 +Wang wang W Wa Wan Wang g ng ang Wang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 10 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 8 BLOCKIN 10 0 +Memory memory M Me Mem Memo y ry ory mory LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 10 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 10 8 BLOCKIN 10 0 +space space s sp spa spac e ce ace pace LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 10 0 +visual visual v vi vis visu l al ual sual LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 4 0 +prompting prompting p pr pro prom g ng ing ting LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 6 BLOCKIN 4 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 4 0 +efficient efficient e ef eff effi t nt ent ient LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 4 0 +vision vision v vi vis visi n on ion sion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 6 6 BLOCKIN 4 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 6 BLOCKIN 4 0 +fine fine f fi fin fine e ne ine fine LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 8 6 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 8 6 BLOCKIN 4 0 +tuning tuning t tu tun tuni g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 4 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 4 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 4 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +96 96 9 96 96 96 6 96 96 96 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Kai kai K Ka Kai Kai i ai Kai Kai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +Lv lv L Lv Lv Lv v Lv Lv Lv LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 8 0 +Yuqing yuqing Y Yu Yuq Yuqi g ng ing qing LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +Yang yang Y Ya Yan Yang g ng ang Yang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Tengxiao tengxiao T Te Ten Teng o ao iao xiao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Liu liu L Li Liu Liu u iu Liu Liu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 8 0 +Qinghui qinghui Q Qi Qin Qing i ui hui ghui LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +Gao gao G Ga Gao Gao o ao Gao Gao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 8 0 +Qipeng qipeng Q Qi Qip Qipe g ng eng peng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +Guo guo G Gu Guo Guo o uo Guo Guo LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 8 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +Xipeng xipeng X Xi Xip Xipe g ng eng peng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +Qiu qiu Q Qi Qiu Qiu u iu Qiu Qiu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 9 BLOCKIN 8 0 +Full full F Fu Ful Full l ll ull Full LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +parameter parameter p pa par para r er ter eter LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +fine fine f fi fin fine e ne ine fine LINESTART LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 0 6 BLOCKIN 3 0 +tuning tuning t tu tun tuni g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 3 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 6 BLOCKIN 3 0 +large large l la lar larg e ge rge arge LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 3 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 3 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 6 BLOCKIN 3 0 +with with w wi wit with h th ith with LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 3 0 +limited limited l li lim limi d ed ted ited LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 6 BLOCKIN 3 0 +resources resources r re res reso s es ces rces LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 3 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 3 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 3 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 3 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +97 97 9 97 97 97 7 97 97 97 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Sadhika sadhika S Sa Sad Sadh a ka ika hika LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Malladi malladi M Ma Mal Mall i di adi ladi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 9 0 +Tianyu tianyu T Ti Tia Tian u yu nyu anyu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Gao gao G Ga Gao Gao o ao Gao Gao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Eshaan eshaan E Es Esh Esha n an aan haan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Nichani nichani N Ni Nic Nich i ni ani hani LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 9 0 +Alex alex A Al Ale Alex x ex lex Alex LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +Damian damian D Da Dam Dami n an ian mian LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 9 0 +Jason jason J Ja Jas Jaso n on son ason LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +D d D D D D D D D D LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 9 BLOCKIN 9 0 +Lee lee L Le Lee Lee e ee Lee Lee LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 9 BLOCKIN 9 0 +Danqi danqi D Da Dan Danq i qi nqi anqi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Chen chen C Ch Che Chen n en hen Chen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 9 0 +and and a an and and d nd and and LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Sanjeev sanjeev S Sa San Sanj v ev eev jeev LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 7 BLOCKIN 4 0 +Arora arora A Ar Aro Aror a ra ora rora LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 7 BLOCKIN 4 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 1 7 BLOCKIN 4 0 +Fine fine F Fi Fin Fine e ne ine Fine LINEIN LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 2 7 BLOCKIN 4 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 7 BLOCKIN 4 0 +tuning tuning t tu tun tuni g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 7 BLOCKIN 4 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 7 BLOCKIN 4 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 7 BLOCKIN 4 0 +with with w wi wit with h th ith with LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 7 BLOCKIN 4 0 +just just j ju jus just t st ust just LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 7 BLOCKIN 4 0 +forward forward f fo for forw d rd ard ward LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 7 BLOCKIN 4 0 +passes passes p pa pas pass s es ses sses LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 7 BLOCKIN 4 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 7 BLOCKIN 4 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 7 BLOCKIN 4 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 7 BLOCKEND 4 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +98 98 9 98 98 98 8 98 98 98 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Gang gang G Ga Gan Gang g ng ang Gang LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Liu liu L Li Liu Liu u iu Liu Liu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 9 0 +Jinlong jinlong J Ji Jin Jinl g ng ong long LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +He he H He He He e He He He LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Pengfei pengfei P Pe Pen Peng i ei fei gfei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Li li L Li Li Li i Li Li Li LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 9 0 +Genrong genrong G Ge Gen Genr g ng ong rong LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +He he H He He He e He He He LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 9 0 +Zhaolin zhaolin Z Zh Zha Zhao n in lin olin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +Chen chen C Ch Che Chen n en hen Chen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 9 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +Shenjun shenjun S Sh She Shen n un jun njun LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +Zhong zhong Z Zh Zho Zhon g ng ong hong LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKIN 9 0 +Pefomed pefomed P Pe Pef Pefo d ed med omed LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +: : : : : : : : : : LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 10 9 BLOCKIN 9 0 +Parameter parameter P Pa Par Para r er ter eter LINESTART LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 3 0 +efficient efficient e ef eff effi t nt ent ient LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 3 0 +fine fine f fi fin fine e ne ine fine LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 9 BLOCKIN 3 0 +tuning tuning t tu tun tuni g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 3 0 +of of o of of of f of of of LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 3 0 +multimodal multimodal m mu mul mult l al dal odal LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 3 0 +large large l la lar larg e ge rge arge LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 3 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 3 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 3 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 3 0 +medical medical m me med medi l al cal ical LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 3 0 +imaging imaging i im ima imag g ng ing ging LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 3 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 3 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 9 BLOCKIN 3 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKEND 3 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +99 99 9 99 99 99 9 99 99 99 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Wei wei W We Wei Wei i ei Wei Wei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 1 9 BLOCKIN 9 0 +Ning ning N Ni Nin Ning g ng ing Ning LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Hsu hsu H Hs Hsu Hsu u su Hsu Hsu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 9 0 +Benjamin benjamin B Be Ben Benj n in min amin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +Bolte bolte B Bo Bol Bolt e te lte olte LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Yao yao Y Ya Yao Yao o ao Yao Yao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 4 9 BLOCKIN 9 0 +Hung hung H Hu Hun Hung g ng ung Hung LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Hubert hubert H Hu Hub Hube t rt ert bert LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Tsai tsai T Ts Tsa Tsai i ai sai Tsai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 9 0 +Kushal kushal K Ku Kus Kush l al hal shal LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +Lakhotia lakhotia L La Lak Lakh a ia tia otia LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 9 0 +Ruslan ruslan R Ru Rus Rusl n an lan slan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +Salakhutdinov salakhutdinov S Sa Sal Sala v ov nov inov LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +, , , , , , , , , , LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 9 0 +and and a an and and d nd and and LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 3 0 +Abdelrahman abdelrahman A Ab Abd Abde n an man hman LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 3 0 +Mohamed mohamed M Mo Moh Moha d ed med amed LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 3 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 2 8 BLOCKIN 3 0 +Hubert hubert H Hu Hub Hube t rt ert bert LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 3 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 3 8 BLOCKIN 3 0 +Self self S Se Sel Self f lf elf Self LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 4 8 BLOCKIN 3 0 +supervised supervised s su sup supe d ed sed ised LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 3 0 +speech speech s sp spe spee h ch ech eech LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 3 0 +representation representation r re rep repr n on ion tion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 3 0 +learning learning l le lea lear g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 3 0 +by by b by by by y by by by LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 3 0 +masked masked m ma mas mask d ed ked sked LINEEND LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 3 0 +prediction prediction p pr pre pred n on ion tion LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 3 BLOCKIN 2 0 +of of o of of of f of of of LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 3 BLOCKIN 2 0 +hidden hidden h hi hid hidd n en den dden LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 3 BLOCKIN 2 0 +units units u un uni unit s ts its nits LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 3 BLOCKIN 2 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 3 BLOCKIN 2 0 +2021 2021 2 20 202 2021 1 21 021 2021 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 3 BLOCKIN 2 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 3 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +100 100 1 10 100 100 0 00 100 100 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Alexei alexei A Al Ale Alex i ei xei exei LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +Baevski baevski B Ba Bae Baev i ki ski vski LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Henry henry H He Hen Henr y ry nry enry LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +Zhou zhou Z Zh Zho Zhou u ou hou Zhou LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 8 0 +Abdelrahman abdelrahman A Ab Abd Abde n an man hman LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +Mohamed mohamed M Mo Moh Moha d ed med amed LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 8 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Michael michael M Mi Mic Mich l el ael hael LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +Auli auli A Au Aul Auli i li uli Auli LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 8 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 9 BLOCKIN 8 0 +wav2vec wav2vec w wa wav wav2 c ec vec 2vec LINEIN ALIGNEDLEFT NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +2 2 2 2 2 2 2 2 2 2 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 9 BLOCKIN 8 0 +0 0 0 0 0 0 0 0 0 0 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 8 0 +: : : : : : : : : : LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 9 9 BLOCKIN 8 0 +A a A A A A A A A A LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +framework framework f fr fra fram k rk ork work LINEEND ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 8 0 +for for f fo for for r or for for LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 3 0 +self self s se sel self f lf elf self LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 1 6 BLOCKIN 3 0 +supervised supervised s su sup supe d ed sed ised LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 3 0 +learning learning l le lea lear g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 3 0 +of of o of of of f of of of LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 6 BLOCKIN 3 0 +speech speech s sp spe spee h ch ech eech LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 3 0 +representations representations r re rep repr s ns ons ions LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 3 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 3 0 +2020 2020 2 20 202 2020 0 20 020 2020 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 3 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 3 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 1 BLOCKSTART 2 0 +101 101 1 10 101 101 1 01 101 101 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 1 BLOCKIN 2 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 3 1 BLOCKIN 2 0 +Deepak deepak D De Dee Deep k ak pak epak LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 1 BLOCKIN 2 0 +Babu babu B Ba Bab Babu u bu abu Babu LINESTART LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 0 BLOCKIN no 0 +P p P P P P P P P P LINESTART LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 3 0 BLOCKIN no 0 +R r R R R R R R R R LINESTART LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 2 0 BLOCKIN 1 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 5 0 BLOCKIN 1 0 +Audio audio A Au Aud Audi o io dio udio LINESTART LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 0 BLOCKIN no 0 +language language l la lan lang e ge age uage LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 0 BLOCKIN no 0 +models models m mo mod mode s ls els dels LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 0 BLOCKIN no 0 +and and a an and and d nd and and LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 0 BLOCKIN no 0 +multimodal multimodal m mu mul mult l al dal odal LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 1 BLOCKIN no 0 +ar ar a ar ar ar r ar ar ar LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 0 BLOCKIN 1 0 +- - - - - - - - - - LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 7 0 BLOCKIN 1 0 +chitecture chitecture c ch chi chit e re ure ture LINESTART ALIGNEDLEFT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 1 BLOCKIN no 0 +- - - - - - - - - - LINESTART LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 5 0 BLOCKIN 1 0 +prdeepak prdeepak p pr prd prde k ak pak epak LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 1 BLOCKIN 2 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 5 1 BLOCKIN 2 0 +babu babu b ba bab babu u bu abu babu LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 1 BLOCKIN 2 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 1 BLOCKIN 2 0 +https https h ht htt http s ps tps ttps LINESTART LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 1 NOPUNCT 1 3 BLOCKIN 8 0 +: : : : : : : : : : LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 PUNCT 1 3 BLOCKIN 8 0 +/ / / / / / / / / / LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 1 3 BLOCKIN 8 0 +/ / / / / / / / / / LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 2 3 BLOCKIN 8 0 +medium medium m me med medi m um ium dium LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 3 BLOCKIN 8 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 4 3 BLOCKIN 8 0 +com com c co com com m om com com LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 3 BLOCKIN 8 0 +/ / / / / / / / / / LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 5 3 BLOCKIN 8 0 +@ @ @ @ @ @ @ @ @ @ LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 5 3 BLOCKIN 8 0 +prdeepak prdeepak p pr prd prde k ak pak epak LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 3 BLOCKIN 8 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 8 3 BLOCKIN 8 0 +babu babu b ba bab babu u bu abu babu LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 3 BLOCKIN 8 0 +/ / / / / / / / / / LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 9 3 BLOCKIN 8 0 +audio audio a au aud audi o io dio udio LINESTART ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 0 6 BLOCKIN 7 0 +language language l la lan lang e ge age uage LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 2 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 2 6 BLOCKIN 7 0 +models models m mo mod mode s ls els dels LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 3 6 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 4 6 BLOCKIN 7 0 +multimodal multimodal m mu mul mult l al dal odal LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 5 6 BLOCKIN 7 0 +architecture architecture a ar arc arch e re ure ture LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 6 BLOCKIN 7 0 +- - - - - - - - - - LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 7 6 BLOCKIN 7 0 +1cdd90f46fac 1cdd90f46fac 1 1c 1cd 1cdd c ac fac 6fac LINEIN ALIGNEDLEFT NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 7 0 +. . . . . . . . . . LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 9 6 BLOCKIN 7 0 +[ [ [ [ [ [ [ [ [ [ LINESTART LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 1 BLOCKIN 3 0 +Accessed accessed A Ac Acc Acce d ed sed ssed LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 1 BLOCKIN 3 0 +19 19 1 19 19 19 9 19 19 19 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 7 1 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 8 1 BLOCKIN 3 0 +07 07 0 07 07 07 7 07 07 07 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 1 BLOCKIN 3 0 +- - - - - - - - - - LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 10 1 BLOCKIN 3 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINESTART ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 5 0 BLOCKIN 2 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 6 0 BLOCKIN 2 0 +. . . . . . . . . . LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 0 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 8 0 +102 102 1 10 102 102 2 02 102 102 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 8 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 8 0 +Paul paul P Pa Pau Paul l ul aul Paul LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +K k K K K K K K K K LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 8 0 +. . . . . . . . . . LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 1 9 BLOCKIN 8 0 +Rubenstein rubenstein R Ru Rub Rube n in ein tein LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 8 0 +Chulayuth chulayuth C Ch Chu Chul h th uth yuth LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 8 0 +Asawaroengchai asawaroengchai A As Asa Asaw i ai hai chai LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 8 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 5 9 BLOCKIN 8 0 +Duc duc D Du Duc Duc c uc Duc Duc LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Dung dung D Du Dun Dung g ng ung Dung LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 8 0 +Nguyen nguyen N Ng Ngu Nguy n en yen uyen LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 8 0 +, , , , , , , , , 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LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 2 9 BLOCKIN 5 0 +End end E En End End d nd End End LINEIN LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 5 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 3 9 BLOCKIN 5 0 +to to t to to to o to to to LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 5 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 3 9 BLOCKIN 5 0 +end end e en end end d nd end end LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 5 0 +learnable learnable l le lea lear e le ble able LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 5 0 +clustering clustering c cl clu clus g ng ing ring LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +for for f fo for for r or for for LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 5 0 +intent intent i in int inte t nt ent tent LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 5 0 +learning learning l le lea lear g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 5 0 +in in i in in in n in in in LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 5 0 +recommendation recommendation r re rec reco n on ion tion LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 5 0 +, , , , , , , , , , LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 5 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINESTART LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 5 0 BLOCKIN 1 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 7 0 BLOCKEND 1 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 9 0 +110 110 1 11 110 110 0 10 110 110 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 9 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 9 0 +Haoran haoran H Ha Hao Haor n an ran oran LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +Li li L Li Li Li i Li Li Li LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 1 9 BLOCKIN 9 0 +Xinyuan xinyuan X Xi Xin Xiny n an uan yuan LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 9 0 +Zhao zhao Z Zh Zha Zhao o ao hao Zhao LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 3 9 BLOCKIN 9 0 +Dadi dadi D Da Dad Dadi i di adi Dadi LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +Guo guo G Gu Guo Guo o uo Guo Guo LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 9 0 +Hanlin hanlin H Ha Han Hanl n in lin nlin LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +Gu gu G Gu Gu Gu u Gu Gu Gu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 9 0 +Ziqian ziqian Z Zi Ziq Ziqi n an ian qian LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 9 0 +Zeng zeng Z Ze Zen Zeng g ng eng Zeng LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 9 BLOCKIN 9 0 +Yuxing yuxing Y Yu Yux Yuxi g ng ing xing LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +Han han H Ha Han Han n an Han Han LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 9 0 +Yangqiu yangqiu Y Ya Yan Yang u iu qiu gqiu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 9 0 +Song song S So Son Song g ng ong Song LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 10 9 BLOCKIN 9 0 +Lixin lixin L Li Lix Lixi n in xin ixin LINEEND ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 9 0 +Fan fan F Fa Fan Fan n an Fan Fan LINESTART LINEINDENT INITCAP NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 3 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 0 8 BLOCKIN 3 0 +and and a an and and d nd and and LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 0 8 BLOCKIN 3 0 +Qiang qiang Q Qi Qia Qian g ng ang iang LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 8 BLOCKIN 3 0 +Yang yang Y Ya Yan Yang g ng ang Yang LINEIN LINEINDENT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 2 8 BLOCKIN 3 0 +. . . . . . . . . . LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 2 8 BLOCKIN 3 0 +Federated federated F Fe Fed Fede d ed ted ated LINEIN LINEINDENT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 8 BLOCKIN 3 0 +domain domain d do dom doma n in ain main LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 8 BLOCKIN 3 0 +- - - - - - - - - - LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 HYPHEN 4 8 BLOCKIN 3 0 +specific specific s sp spe spec c ic fic ific LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 8 BLOCKIN 3 0 +knowledge knowledge k kn kno know e ge dge edge LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 8 BLOCKIN 3 0 +transfer transfer t tr tra tran r er fer sfer LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 8 BLOCKIN 3 0 +on on o on on on n on on on LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 8 8 BLOCKIN 3 0 +large large l la lar larg e ge rge arge LINEIN LINEINDENT NOCAPS NODIGIT 0 1 1 0 0 0 0 0 NOPUNCT 9 8 BLOCKIN 3 0 +language language l la lan lang e ge age uage LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 3 0 +models models m mo mod mode s ls els dels LINEEND LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 10 8 BLOCKIN 3 0 +using using u us usi usin g ng ing sing LINESTART LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 2 BLOCKIN 2 0 +synthetic synthetic s sy syn synt c ic tic etic LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 5 2 BLOCKIN 2 0 +data data d da dat data a ta ata data LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 7 2 BLOCKIN 2 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 7 2 BLOCKIN 2 0 +2024 2024 2 20 202 2024 4 24 024 2024 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 2 BLOCKIN 2 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 2 BLOCKEND 2 0 +[ [ [ [ [ [ [ [ [ [ LINESTART ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 OPENBRACKET 0 9 BLOCKSTART 7 0 +111 111 1 11 111 111 1 11 111 111 LINEIN ALIGNEDLEFT NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 NOPUNCT 0 9 BLOCKIN 7 0 +] ] ] ] ] ] ] ] ] ] LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 ENDBRACKET 0 9 BLOCKIN 7 0 +Aleksander aleksander A Al Ale Alek r er der nder LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 1 9 BLOCKIN 7 0 +Madry madry M Ma Mad Madr y ry dry adry LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 2 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 2 9 BLOCKIN 7 0 +Aleksandar aleksandar A Al Ale Alek r ar dar ndar LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 3 9 BLOCKIN 7 0 +Makelov makelov M Ma Mak Make v ov lov elov LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 4 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 4 9 BLOCKIN 7 0 +Ludwig ludwig L Lu Lud Ludw g ig wig dwig LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 5 9 BLOCKIN 7 0 +Schmidt schmidt S Sc Sch Schm t dt idt midt LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 6 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 6 9 BLOCKIN 7 0 +Dimitris dimitris D Di Dim Dimi s is ris tris LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 7 9 BLOCKIN 7 0 +Tsipras tsipras T Ts Tsi Tsip s as ras pras LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 9 BLOCKIN 7 0 +, , , , , , , , , , LINEIN ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 8 9 BLOCKIN 7 0 +and and a an and and d nd and and LINEIN ALIGNEDLEFT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 9 BLOCKIN 7 0 +Adrian adrian A Ad Adr Adri n an ian rian LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 1 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 7 0 +Vladu vladu V Vl Vla Vlad u du adu ladu LINEIN ALIGNEDLEFT INITCAP NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 10 9 BLOCKIN 7 0 +. . . . . . . . . . LINEEND ALIGNEDLEFT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 9 BLOCKIN 7 0 +Towards towards T To Tow Towa s ds rds ards LINESTART LINEINDENT INITCAP NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 2 0 +deep deep d de dee deep p ep eep deep LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 1 6 BLOCKIN 2 0 +learning learning l le lea lear g ng ing ning LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 3 6 BLOCKIN 2 0 +models models m mo mod mode s ls els dels LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 4 6 BLOCKIN 2 0 +resistant resistant r re res resi t nt ant tant LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 2 0 +to to t to to to o to to to LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 6 6 BLOCKIN 2 0 +adversarial adversarial a ad adv adve l al ial rial LINEIN LINEINDENT NOCAPS NODIGIT 0 0 0 0 0 0 0 0 NOPUNCT 8 6 BLOCKIN 2 0 +attacks attacks a at att atta s ks cks acks LINEIN LINEINDENT NOCAPS NODIGIT 0 0 1 0 0 0 0 0 NOPUNCT 9 6 BLOCKIN 2 0 +, , , , , , , , , , LINEIN LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 COMMA 9 6 BLOCKIN 2 0 +2019 2019 2 20 201 2019 9 19 019 2019 LINEIN LINEINDENT NOCAPS ALLDIGIT 0 0 0 0 0 1 0 0 NOPUNCT 10 6 BLOCKIN 2 0 +. . . . . . . . . . LINEEND LINEINDENT ALLCAP NODIGIT 1 0 0 0 0 0 0 0 DOT 10 6 BLOCKEND 2 0 + diff --git a/grobid-core/src/test/java/org/grobid/core/GrobidModelsTest.java b/grobid-core/src/test/java/org/grobid/core/GrobidModelsTest.java index e28b62ca56..79c9198d03 100644 --- a/grobid-core/src/test/java/org/grobid/core/GrobidModelsTest.java +++ b/grobid-core/src/test/java/org/grobid/core/GrobidModelsTest.java @@ -1,5 +1,6 @@ package org.grobid.core; +import org.grobid.core.utilities.TestEngineUtils; import org.grobid.core.utilities.GrobidConfig; import org.grobid.core.utilities.GrobidProperties; import org.junit.BeforeClass; @@ -12,6 +13,7 @@ public class GrobidModelsTest { @BeforeClass public static void setInitialContext() throws Exception { + TestEngineUtils.initGrobidForceWapiti(); GrobidProperties.getInstance(); } @@ -24,7 +26,7 @@ public void testGrobidModelsEnum_StandardModel_affiliation() throws Exception { assertThat(model.getModelName(), is("affiliation-address")); assertThat(model.getTemplateName(), is("affiliation-address.template")); String[] splittedPath = model.getModelPath().split("[/\\\\]"); - //assertThat(splittedPath[splittedPath.length - 1], is("model.wapiti")); + assertThat(splittedPath[splittedPath.length - 1], is("model.wapiti")); assertThat(splittedPath[splittedPath.length - 2], is("affiliation-address")); assertThat(splittedPath[splittedPath.length - 3], is("models")); } @@ -37,7 +39,7 @@ public void testGrobidModelsEnum_StandardModel_name() throws Exception { assertThat(model.getModelName(), is("header")); assertThat(model.getTemplateName(), is("header.template")); String[] splittedPath = model.getModelPath().split("[/\\\\]"); - //assertThat(splittedPath[splittedPath.length - 1], is("model.wapiti")); + assertThat(splittedPath[splittedPath.length - 1], is("model.wapiti")); assertThat(splittedPath[splittedPath.length - 2], is("header")); assertThat(splittedPath[splittedPath.length - 4], is("grobid-home")); } @@ -56,7 +58,7 @@ public void testGrobidModelsEnum_CustomModel_shouldBeConfiguredBeforeHand() thro assertThat(model.getTemplateName(), is("myDreamModel.template")); String[] tokenizePath = model.getModelPath().split("[/\\\\]"); - //assertThat(tokenizePath[tokenizePath.length - 1], is("model.wapiti")); + assertThat(tokenizePath[tokenizePath.length - 1], is("model.wapiti")); assertThat(tokenizePath[tokenizePath.length - 2], is("myDreamModel")); assertThat(tokenizePath[tokenizePath.length - 3], is("models")); assertThat(tokenizePath[tokenizePath.length - 4], is("grobid-home")); diff --git a/grobid-core/src/test/java/org/grobid/core/data/AffiliationTest.java b/grobid-core/src/test/java/org/grobid/core/data/AffiliationTest.java new file mode 100644 index 0000000000..e69de29bb2 diff --git a/grobid-core/src/test/java/org/grobid/core/data/FigureTest.java b/grobid-core/src/test/java/org/grobid/core/data/FigureTest.java new file mode 100644 index 0000000000..e69de29bb2 diff --git a/grobid-core/src/test/java/org/grobid/core/data/FunderTest.java b/grobid-core/src/test/java/org/grobid/core/data/FunderTest.java new file mode 100644 index 0000000000..e69de29bb2 diff --git a/grobid-core/src/test/java/org/grobid/core/data/FundingTest.java b/grobid-core/src/test/java/org/grobid/core/data/FundingTest.java new file mode 100644 index 0000000000..e69de29bb2 diff --git a/grobid-core/src/test/java/org/grobid/core/data/PersonTest.java b/grobid-core/src/test/java/org/grobid/core/data/PersonTest.java new file mode 100644 index 0000000000..9a432c0aee --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/data/PersonTest.java @@ -0,0 +1,234 @@ +package org.grobid.core.data; + +import org.junit.Before; +import org.junit.Test; + +import java.util.Arrays; +import java.util.List; + +import static org.hamcrest.CoreMatchers.*; +import static org.hamcrest.MatcherAssert.assertThat; +import static org.hamcrest.Matchers.hasSize; + +public class PersonTest { + + private Person person; + + @Before + public void setUp() { + person = new Person(); + } + + @Test + public void testSetFirstName() { + person.setFirstName("John"); + assertThat(person.getFirstName(), is("John")); + } + + @Test + public void testSetLastName() { + person.setLastName("Doe"); + assertThat(person.getLastName(), is("Doe")); + } + + @Test + public void testSetMiddleName() { + person.setMiddleName("Michael"); + assertThat(person.getMiddleName(), is("Michael")); + } + + @Test + public void testSetRawName() { + person.setRawName("John M. Doe"); + assertThat(person.getRawName(), is("John M. Doe")); + } + + @Test + public void testSetTitle_withParentheses_shouldRemoveThem() { + person.setTitle("(Prof.)"); + assertThat(person.getTitle(), is("Prof.")); + } + + @Test + public void testSetTitle_withMultipleParentheses_shouldRemoveAll() { + person.setTitle("((Dr.))"); + assertThat(person.getTitle(), is("Dr.")); + } + + @Test + public void testSetTitle_withoutParentheses() { + person.setTitle("Dr."); + assertThat(person.getTitle(), is("Dr.")); + } + + @Test + public void testSetSuffix() { + person.setSuffix("Jr."); + assertThat(person.getSuffix(), is("Jr.")); + } + + @Test + public void testSetCorresp() { + person.setCorresp(true); + assertThat(person.getCorresp(), is(true)); + } + + @Test + public void testSetORCID_withHttpPrefix_shouldRemovePrefix() { + person.setORCID("http://orcid.org/0000-0001-2345-6789"); + assertThat(person.getORCID(), is("0000-0001-2345-6789")); + } + + @Test + public void testSetORCID_withHttpsPrefix_shouldRemovePrefix() { + person.setORCID("https://orcid.org/0000-0001-2345-6789"); + assertThat(person.getORCID(), is("0000-0001-2345-6789")); + } + + @Test + public void testSetORCID_withoutPrefix() { + person.setORCID("0000-0001-2345-6789"); + assertThat(person.getORCID(), is("0000-0001-2345-6789")); + } + + @Test + public void testSetORCID_null_shouldNotThrow() { + person.setORCID(null); + assertThat(person.getORCID(), is(nullValue())); + } + + @Test + public void testSetEmail() { + person.setEmail("john.doe@example.com"); + assertThat(person.getEmail(), is("john.doe@example.com")); + } + + @Test + public void testNotNull_allFieldsNull_shouldReturnFalse() { + assertThat(person.notNull(), is(false)); + } + + @Test + public void testNotNull_withFirstName_shouldReturnTrue() { + person.setFirstName("John"); + assertThat(person.notNull(), is(true)); + } + + @Test + public void testNotNull_withLastName_shouldReturnTrue() { + person.setLastName("Doe"); + assertThat(person.notNull(), is(true)); + } + + @Test + public void testNotNull_withMiddleName_shouldReturnTrue() { + person.setMiddleName("Michael"); + assertThat(person.notNull(), is(true)); + } + + @Test + public void testNotNull_withTitle_shouldReturnTrue() { + person.setTitle("Dr."); + assertThat(person.notNull(), is(true)); + } + + @Test + public void testAddAffiliationMarker() { + person.addAffiliationMarker("1"); + person.addAffiliationMarker("2"); + + List markers = person.getAffiliationMarkers(); + assertThat(markers, hasSize(2)); + assertThat(markers.get(0), is("1")); + assertThat(markers.get(1), is("2")); + } + + @Test + public void testAddMarker_shouldRemoveSpaces() { + person.addMarker("1 2"); + + List markers = person.getMarkers(); + assertThat(markers, hasSize(1)); + assertThat(markers.get(0), is("12")); + } + + @Test + public void testAddAffiliation() { + Affiliation affiliation = new Affiliation(); + affiliation.setName("MIT"); + + person.addAffiliation(affiliation); + + List affiliations = person.getAffiliations(); + assertThat(affiliations, hasSize(1)); + assertThat(affiliations.get(0).getName(), is("MIT")); + } + + @Test + public void testClonePerson() { + person.setFirstName("John"); + person.setLastName("Doe"); + person.setMiddleName("Michael"); + person.setEmail("john@example.com"); + person.setORCID("0000-0001-2345-6789"); + person.setCorresp(true); + + Person cloned = person.clonePerson(); + + assertThat(cloned.getFirstName(), is("John")); + assertThat(cloned.getLastName(), is("Doe")); + assertThat(cloned.getMiddleName(), is("Michael")); + assertThat(cloned.getEmail(), is("john@example.com")); + assertThat(cloned.getORCID(), is("0000-0001-2345-6789")); + assertThat(cloned.getCorresp(), is(true)); + } + + @Test + public void testSetAffiliationBlocks() { + List blocks = Arrays.asList("block1", "block2"); + person.setAffiliationBlocks(blocks); + + assertThat(person.getAffiliationBlocks(), is(blocks)); + } + + @Test + public void testAddAffiliationBlocks() { + person.addAffiliationBlocks("block1"); + person.addAffiliationBlocks("block2"); + + List blocks = person.getAffiliationBlocks(); + assertThat(blocks, hasSize(2)); + } + + @Test + public void testSetMarkers() { + List markers = Arrays.asList("1", "2", "3"); + person.setMarkers(markers); + + assertThat(person.getMarkers(), is(markers)); + } + + @Test + public void testSetAffiliationMarkers() { + List markers = Arrays.asList("a", "b"); + person.setAffiliationMarkers(markers); + + assertThat(person.getAffiliationMarkers(), is(markers)); + } + + @Test + public void testSetAffiliations() { + Affiliation aff1 = new Affiliation(); + aff1.setName("MIT"); + Affiliation aff2 = new Affiliation(); + aff2.setName("Stanford"); + + List affiliations = Arrays.asList(aff1, aff2); + person.setAffiliations(affiliations); + + assertThat(person.getAffiliations(), hasSize(2)); + assertThat(person.getAffiliations().get(0).getName(), is("MIT")); + assertThat(person.getAffiliations().get(1).getName(), is("Stanford")); + } +} + diff --git a/grobid-core/src/test/java/org/grobid/core/data/TableTest.java b/grobid-core/src/test/java/org/grobid/core/data/TableTest.java new file mode 100644 index 0000000000..e69de29bb2 diff --git a/grobid-core/src/test/java/org/grobid/core/document/TEIFormatterIntegrationTest.java b/grobid-core/src/test/java/org/grobid/core/document/TEIFormatterIntegrationTest.java index 159a254e18..2fa793b584 100644 --- a/grobid-core/src/test/java/org/grobid/core/document/TEIFormatterIntegrationTest.java +++ b/grobid-core/src/test/java/org/grobid/core/document/TEIFormatterIntegrationTest.java @@ -3,8 +3,7 @@ import org.grobid.core.data.Note; import org.grobid.core.engines.EngineParsers; import org.grobid.core.engines.config.GrobidAnalysisConfig; -import org.grobid.core.main.LibraryLoader; -import org.grobid.core.utilities.GrobidProperties; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.BeforeClass; import org.junit.Test; @@ -12,15 +11,14 @@ import java.util.List; import static org.hamcrest.CoreMatchers.is; +import static org.hamcrest.MatcherAssert.assertThat; import static org.hamcrest.Matchers.hasSize; -import static org.junit.Assert.assertThat; public class TEIFormatterIntegrationTest { @BeforeClass public static void setInitialContext() throws Exception { - GrobidProperties.getInstance(); - LibraryLoader.load(); + TestEngineUtils.initGrobidForceWapiti(); } @Test @@ -31,10 +29,10 @@ public void testGetTeiNotes() throws Exception { List teiNotes = new TEIFormatter(null, null).getTeiNotes(doc); - /*assertThat(teiNotes, hasSize(1)); - assertThat(teiNotes.get(0).getText(), is(" http://wikipedia.org ")); + assertThat(teiNotes, hasSize(1)); + assertThat(teiNotes.get(0).getText(), is("http://wikipedia.org ")); assertThat(teiNotes.get(0).getLabel(), is("1")); - assertThat(teiNotes.get(0).getPageNumber(), is(1));*/ + assertThat(teiNotes.get(0).getPageNumber(), is(1)); } } \ No newline at end of file diff --git a/grobid-core/src/test/java/org/grobid/core/engines/DateParserIntegrationTest.java b/grobid-core/src/test/java/org/grobid/core/engines/DateParserIntegrationTest.java index faf07269ec..b74b436400 100644 --- a/grobid-core/src/test/java/org/grobid/core/engines/DateParserIntegrationTest.java +++ b/grobid-core/src/test/java/org/grobid/core/engines/DateParserIntegrationTest.java @@ -1,7 +1,7 @@ package org.grobid.core.engines; import org.grobid.core.data.Date; -import org.grobid.core.factory.AbstractEngineFactory; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.*; import java.util.Arrays; @@ -21,13 +21,7 @@ public class DateParserIntegrationTest { @BeforeClass public static void setInitialContext() throws Exception { -// MockContext.setInitialContext(); - AbstractEngineFactory.init(); - } - - @AfterClass - public static void destroyInitialContext() throws Exception { -// MockContext.destroyInitialContext(); + TestEngineUtils.initGrobidForceWapiti(); } @Before diff --git a/grobid-core/src/test/java/org/grobid/core/engines/SegmentationTest.java b/grobid-core/src/test/java/org/grobid/core/engines/SegmentationTest.java index a09ac407d9..fccc5ce675 100644 --- a/grobid-core/src/test/java/org/grobid/core/engines/SegmentationTest.java +++ b/grobid-core/src/test/java/org/grobid/core/engines/SegmentationTest.java @@ -3,7 +3,7 @@ import org.grobid.core.document.Document; import org.grobid.core.document.DocumentSource; import org.grobid.core.engines.config.GrobidAnalysisConfig; -import org.grobid.core.factory.AbstractEngineFactory; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.AfterClass; import org.junit.Before; import org.junit.BeforeClass; @@ -21,7 +21,7 @@ public class SegmentationTest { @BeforeClass public static void setInitialContext() throws Exception { // MockContext.setInitialContext(); - AbstractEngineFactory.init(); + TestEngineUtils.initGrobidForceWapiti(); } @AfterClass diff --git a/grobid-core/src/test/java/org/grobid/core/engines/patent/ReferenceExtractorTest.java b/grobid-core/src/test/java/org/grobid/core/engines/patent/ReferenceExtractorTest.java index fc64da641d..abb010a382 100644 --- a/grobid-core/src/test/java/org/grobid/core/engines/patent/ReferenceExtractorTest.java +++ b/grobid-core/src/test/java/org/grobid/core/engines/patent/ReferenceExtractorTest.java @@ -10,8 +10,7 @@ import org.grobid.core.data.BibDataSet; import org.grobid.core.data.PatentItem; -import org.grobid.core.factory.AbstractEngineFactory; -import org.grobid.core.utilities.counters.GrobidTimer; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.AfterClass; import org.junit.BeforeClass; import org.junit.Ignore; @@ -26,7 +25,7 @@ public class ReferenceExtractorTest { @BeforeClass public static void setInitialContext() throws Exception { - AbstractEngineFactory.init(); + TestEngineUtils.initGrobidForceWapiti(); } @AfterClass diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/CRFDecoderTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/CRFDecoderTest.java new file mode 100644 index 0000000000..dacaac654d --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/CRFDecoderTest.java @@ -0,0 +1,220 @@ +package org.grobid.core.engines.tagging.delft; + +import org.junit.Before; +import org.junit.Test; + +import static org.junit.Assert.*; + +/** + * Unit tests for CRFDecoder Viterbi decoding. + * + * Tests verify: + * - Basic Viterbi decoding finds optimal path + * - Mask handling for variable length sequences + * - Transition matrix usage + * - Start/end transitions + * - Batch decoding + */ +public class CRFDecoderTest { + + private CRFDecoder decoder; + + @Before + public void setUp() { + // Create a simple 3-tag CRF decoder (O, B-TITLE, I-TITLE) + // Transition matrix [from_tag][to_tag] + float[][] transitions = { + // to: O, B-TITLE, I-TITLE + { 0.5f, 0.3f, -1.0f }, // from O: prefer O or B-TITLE, penalize I-TITLE + { 0.2f, 0.1f, 0.6f }, // from B-TITLE: prefer I-TITLE + { 0.3f, 0.1f, 0.5f } // from I-TITLE: prefer continuing I-TITLE + }; + + // Start transitions: prefer starting with O or B-TITLE + float[] startTransitions = { 0.5f, 0.4f, -1.0f }; + + // End transitions: all tags can end + float[] endTransitions = { 0.0f, 0.0f, 0.0f }; + + decoder = new CRFDecoder(transitions, startTransitions, endTransitions); + } + + @Test + public void testGetNumTags() { + assertEquals(3, decoder.getNumTags()); + } + + /** + * Test basic decoding with strong emissions for each tag. + */ + @Test + public void testDecode_followsStrongEmissions() { + // Emissions strongly favor: [O, B-TITLE, I-TITLE, O] + float[][] emissions = { + { 2.0f, -1.0f, -1.0f }, // Position 0: strongly O + { -1.0f, 2.0f, -1.0f }, // Position 1: strongly B-TITLE + { -1.0f, -1.0f, 2.0f }, // Position 2: strongly I-TITLE + { 2.0f, -1.0f, -1.0f }, // Position 3: strongly O + }; + + int[] result = decoder.decode(emissions, null); + + assertEquals(4, result.length); + assertEquals(0, result[0]); // O + assertEquals(1, result[1]); // B-TITLE + assertEquals(2, result[2]); // I-TITLE + assertEquals(0, result[3]); // O + } + + /** + * Test that transitions influence decoding when emissions are ambiguous. + */ + @Test + public void testDecode_transitionsInfluenceDecoding() { + // Emissions are all equal - transitions should decide + float[][] emissions = { + { 0.0f, 0.0f, 0.0f }, // Position 0: ambiguous + { 0.0f, 0.0f, 0.0f }, // Position 1: ambiguous + }; + + int[] result = decoder.decode(emissions, null); + + assertEquals(2, result.length); + // With our transition matrix, starting with O is preferred + // (startTransitions[0]=0.5) + // and O->O has good transition (0.5) + assertEquals(0, result[0]); // Should start with O + } + + /** + * Test that I-TITLE cannot start a sequence (penalized by startTransitions). + */ + @Test + public void testDecode_cannotStartWithContinuation() { + // Position 0 emissions favor I-TITLE, but start transitions penalize it + float[][] emissions = { + { 0.0f, 0.0f, 0.5f }, // Slightly favor I-TITLE + }; + + int[] result = decoder.decode(emissions, null); + + // Should NOT be I-TITLE (index 2) because start transitions penalize it + assertNotEquals(2, result[0]); + } + + /** + * Test decoding with mask - only valid positions are decoded. + */ + @Test + public void testDecode_respectsMask() { + float[][] emissions = { + { 2.0f, -1.0f, -1.0f }, // Position 0: O + { -1.0f, 2.0f, -1.0f }, // Position 1: B-TITLE + { -1.0f, -1.0f, 2.0f }, // Position 2: I-TITLE (masked out) + { 2.0f, -1.0f, -1.0f }, // Position 3: O (masked out) + }; + + boolean[] mask = { true, true, false, false }; + + int[] result = decoder.decode(emissions, mask); + + // Only first 2 positions should be decoded + assertEquals(2, result.length); + assertEquals(0, result[0]); // O + assertEquals(1, result[1]); // B-TITLE + } + + /** + * Test decoding empty sequence (all masked out). + */ + @Test + public void testDecode_emptySequence() { + float[][] emissions = { + { 2.0f, -1.0f, -1.0f }, + { -1.0f, 2.0f, -1.0f }, + }; + + boolean[] mask = { false, false }; + + int[] result = decoder.decode(emissions, mask); + + assertEquals(0, result.length); + } + + /** + * Test batch decoding. + */ + @Test + public void testDecodeBatch() { + float[][][] emissions = { + // Sequence 0: [O, B-TITLE] + { + { 2.0f, -1.0f, -1.0f }, + { -1.0f, 2.0f, -1.0f }, + }, + // Sequence 1: [B-TITLE, I-TITLE] + { + { -1.0f, 2.0f, -1.0f }, + { -1.0f, -1.0f, 2.0f }, + } + }; + + int[][] results = decoder.decodeBatch(emissions, null); + + assertEquals(2, results.length); + + assertEquals(2, results[0].length); + assertEquals(0, results[0][0]); // O + assertEquals(1, results[0][1]); // B-TITLE + + assertEquals(2, results[1].length); + assertEquals(1, results[1][0]); // B-TITLE + assertEquals(2, results[1][1]); // I-TITLE + } + + /** + * Test batch decoding with masks. + */ + @Test + public void testDecodeBatch_withMasks() { + float[][][] emissions = { + // Sequence 0: 3 positions, but only 2 valid + { + { 2.0f, -1.0f, -1.0f }, + { -1.0f, 2.0f, -1.0f }, + { -1.0f, -1.0f, 2.0f }, + }, + // Sequence 1: 3 positions, only 1 valid + { + { 2.0f, -1.0f, -1.0f }, + { -1.0f, 2.0f, -1.0f }, + { -1.0f, -1.0f, 2.0f }, + } + }; + + boolean[][] masks = { + { true, true, false }, + { true, false, false } + }; + + int[][] results = decoder.decodeBatch(emissions, masks); + + assertEquals(2, results[0].length); // 2 valid positions + assertEquals(1, results[1].length); // 1 valid position + } + + /** + * Test single position decoding. + */ + @Test + public void testDecode_singlePosition() { + float[][] emissions = { + { -1.0f, 2.0f, -1.0f }, // Only B-TITLE + }; + + int[] result = decoder.decode(emissions, null); + + assertEquals(1, result.length); + assertEquals(1, result[0]); // B-TITLE + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/HeaderOnnxIntegrationTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/HeaderOnnxIntegrationTest.java new file mode 100644 index 0000000000..e500c532ce --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/HeaderOnnxIntegrationTest.java @@ -0,0 +1,212 @@ +package org.grobid.core.engines.tagging.delft; + +import ai.onnxruntime.OrtException; +import org.apache.commons.lang3.StringUtils; +import org.grobid.core.GrobidModels; +import org.grobid.core.analyzers.GrobidAnalyzer; +import org.grobid.core.features.FeaturesVectorHeader; +import org.grobid.core.layout.LayoutToken; +import org.grobid.core.utilities.GrobidProperties; +import org.junit.*; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import java.util.stream.Collectors; + +import static org.hamcrest.CoreMatchers.is; +import static org.hamcrest.CoreMatchers.notNullValue; +import static org.hamcrest.MatcherAssert.assertThat; +import static org.hamcrest.Matchers.greaterThan; +import static org.hamcrest.Matchers.lessThan; +import static org.junit.Assume.assumeTrue; + +/** + * Integration test for Header ONNX model. + * + * This test verifies that the ONNX-based header model can be loaded and + * run inference correctly. It helps diagnose issues with: + * - ONNX Runtime native library loading + * - LMDB embeddings compatibility + * - CRF decoder functionality + * - End-to-end model inference + * + * Prerequisites: + * - ONNX header model at grobid-home/models/header-BidLSTM_CRF_FEATURES.onnx/ + * - Embeddings preloaded using: python3 + * grobid-home/scripts/preload_embeddings.py --embedding glove-840B + */ +public class HeaderOnnxIntegrationTest { + + private static final String ARCHITECTURE = "BidLSTM_CRF_FEATURES"; + + private static Path modelPath; + private static Path embeddingsPath; + private OnnxSequenceLabellingModel model; + + @BeforeClass + public static void setUpClass() { + // Initialize GROBID properties + GrobidProperties.getInstance(); + + // Get model path + String modelName = GrobidModels.HEADER.getModelName(); + String grobidHome = GrobidProperties.getGrobidHome().getAbsolutePath(); + modelPath = Path.of(grobidHome, "models", modelName + "-" + ARCHITECTURE + ".onnx"); + + // Get embeddings path + String delftPath = GrobidProperties.getDeLFTFilePath(); + embeddingsPath = Path.of(delftPath, "data", "db", "glove-840B"); + } + + @Before + public void setUp() throws IOException, OrtException { + // Skip test if model is not available + assumeTrue("ONNX model not found at " + modelPath + + ". Please ensure the ONNX header model is installed.", + Files.exists(modelPath) && Files.isDirectory(modelPath)); + + // Skip test if embeddings are not available + assumeTrue("Embeddings not found at " + embeddingsPath + + ". Please run: python3 grobid-home/scripts/preload_embeddings.py --embedding glove-840B", + Files.exists(embeddingsPath) && Files.isDirectory(embeddingsPath)); + + // Load model + model = new OnnxSequenceLabellingModel(modelPath); + } + + @After + public void tearDown() { + if (model != null) { + model.close(); + } + } + + @Test + public void testModelCanBeLoaded() { + assertThat(model, is(notNullValue())); + assertThat("Model should have features", model.hasFeatures(), is(true)); + assertThat("Model should have > 0 features", model.getNumFeatures(), greaterThan(0)); + } + + @Test + public void testMaxSequenceLength() { + int maxSeqLength = model.getMaxSeqLength(); + assertThat("Max sequence length should be positive", maxSeqLength, greaterThan(0)); + } + + @Test + public void testAnnotateSimpleHeader() throws OrtException { + String input = "Deep Learning for Natural Language Processing John Smith MIT"; + + List allTokens = GrobidAnalyzer.getInstance().tokenizeWithLayoutToken(input); + List filtered = allTokens.stream() + .filter(token -> StringUtils.isNotBlank(token.getText())) + .collect(Collectors.toList()); + + String[] words = new String[filtered.size()]; + String[][] features = new String[filtered.size()][model.getNumFeatures()]; + for (int i = 0; i < filtered.size(); i++) { + words[i] = filtered.get(i).getText(); + FeaturesVectorHeader featuresVectorHeader = FeaturesVectorHeader.fromLayoutToken(filtered.get(i)); + features[i] = featuresVectorHeader.printVector().split("\n"); + } + + OnnxSequenceLabellingModel.AnnotationResult result = model.annotateTokens(words, features); + + assertThat(result, is(notNullValue())); + assertThat(result.getTokens(), is(notNullValue())); + assertThat(result.getLabels(), is(notNullValue())); + assertThat("Tokens and labels should have same length", + result.getTokens().length, is(result.getLabels().length)); + assertThat(result.getLabels().length, greaterThan(0)); + + long otherLabel = Arrays.stream(result.getLabels()).filter(v -> v.equalsIgnoreCase("")).count(); + + assertThat(otherLabel, lessThan((long) result.getLabels().length)); + } + + @Test + public void testLabelGrobidInput() { + // Create a simple GROBID-formatted input with features + // Format: token\tfeature1\tfeature2\t... + StringBuilder input = new StringBuilder(); + + // Simulate header features (token + 22 features based on config.json) + // Features indices 9-30 = 22 features + String[] tokens = { "Deep", "Learning", "for", "NLP" }; + for (String token : tokens) { + input.append(token); + // Add dummy features (GROBID uses various binary and categorical features) + for (int i = 0; i < 22; i++) { + input.append("\t").append("NOFEAT"); + } + input.append("\n"); + } + + String result = model.labelGrobidInput(input.toString()); + + assertThat(result, is(notNullValue())); + assertThat("Result should not be empty", result.length(), greaterThan(0)); + + // Verify that each line has the original content plus a label + String[] resultLines = result.trim().split("\n"); + assertThat("Result should have same number of lines as input", + resultLines.length, is(tokens.length)); + + for (String line : resultLines) { + String[] parts = line.split("\t"); + // Should have: token + 22 features + 1 label = 24 parts + assertThat("Each line should have at least 24 parts (token + features + label)", + parts.length, greaterThan(23)); + } + } + + @Test + public void testAnnotateTokensWithFeatures() throws OrtException { + // Test token annotation with explicit features + String[] tokens = { "Analysis", "of", "Cancer", "Genomes" }; + // 22 features per token + String[][] features = new String[tokens.length][22]; + for (int i = 0; i < tokens.length; i++) { + for (int j = 0; j < 22; j++) { + features[i][j] = "NOFEAT"; + } + } + + OnnxSequenceLabellingModel.AnnotationResult result = model.annotateTokens(tokens, features); + + assertThat(result, is(notNullValue())); + assertThat(result.getLabels().length, is(tokens.length)); + + assertThat(result.getLabels().length, greaterThan(0)); + + long otherLabel = Arrays.stream(result.getLabels()).filter(v -> v.equalsIgnoreCase("")).count(); + + assertThat(otherLabel, lessThan((long) result.getLabels().length)); + } + + @Test + public void testLabelMultipleSequences() { + // Test with multiple sequences separated by empty lines + StringBuilder input = new StringBuilder(); + + // First sequence + input.append(FeaturesVectorHeader.fromLayoutToken(new LayoutToken("Title")).printVector()); + input.append(FeaturesVectorHeader.fromLayoutToken(new LayoutToken("Text")).printVector()); + input.append("\n"); // Empty line = sequence separator + + // Second sequence + input.append(FeaturesVectorHeader.fromLayoutToken(new LayoutToken("Author")).printVector()); + input.append(FeaturesVectorHeader.fromLayoutToken(new LayoutToken("Name")).printVector()); + + String result = model.labelGrobidInput(input.toString()); + + assertThat(result, is(notNullValue())); + // Result should contain labeled tokens + assertThat("Result should contain labeled output", result.length(), greaterThan(0)); + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModelTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModelTest.java new file mode 100644 index 0000000000..155769d88e --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/OnnxSequenceLabellingModelTest.java @@ -0,0 +1,287 @@ +package org.grobid.core.engines.tagging.delft; + +import org.junit.Test; + +import static org.junit.Assert.*; + +/** + * Unit tests for OnnxSequenceLabellingModel sequence chunking functionality. + */ +public class OnnxSequenceLabellingModelTest { + + /** + * Test that input is correctly split into sequences at empty lines. + */ + @Test + public void testSequenceSplitting() { + String input = "token1\tfeature1\ntoken2\tfeature2\n\ntoken3\tfeature3\ntoken4\tfeature4\n"; + + int sequenceCount = countSequences(input); + + assertEquals(2, sequenceCount); + } + + /** + * Test chunking calculation for large sequences. + */ + @Test + public void testChunkingCalculation() { + int totalTokens = 6748; // Size of large_sequence.txt + int maxSeqLength = 512; + + int expectedChunks = (int) Math.ceil((double) totalTokens / maxSeqLength); + + assertEquals(14, expectedChunks); + } + + /** + * Test that features are correctly parsed from tab-separated lines. + */ + @Test + public void testFeatureParsing() { + String line = "token\tf1\tf2\tf3\tf4"; + String[] parts = line.split("[\\t\\s]+"); + + assertEquals(5, parts.length); + } + + // Helper to count sequences in input + private int countSequences(String input) { + String[] lines = input.split("\n", -1); + int count = 0; + boolean inSequence = false; + + for (String line : lines) { + if (line.trim().isEmpty()) { + if (inSequence) { + count++; + inSequence = false; + } + } else { + inSequence = true; + } + } + if (inSequence) + count++; + + return count; + } + + /** + * Test that feature extraction uses the correct column offset. + * + * Python stores features as: features = pieces[1:] + * So features[9] = pieces[10] + * + * Java must use parts[featureIndex + 1] to get the same value. + * This test verifies the +1 offset logic is correct. + */ + @Test + public void testFeatureExtractionOffset() { + // Simulate Grobid input line with 31 columns (token + 30 features) + // Column 10 = "BLOCKSTART" (0-indexed, so it's pieces[10] in Python) + String line = "token col1 col2 col3 col4 col5 col6 col7 col8 col9 BLOCKSTART LINESTART ALIGNEDLEFT " + + "col13 col14 col15 col16 col17 col18 col19 col20 col21 col22 col23 col24 col25 col26 col27 col28 col29 col30"; + String[] parts = line.split("[\\t\\s]+"); + + // featuresIndices = [9, 10, 11, ...] (Python's 1-based feature indices) + // When we access featureIndex=9, we should get "BLOCKSTART" which is at + // parts[10] + int featureIndex = 9; + int adjustedIndex = featureIndex + 1; // This is the fix! + + assertEquals("BLOCKSTART", parts[adjustedIndex]); + assertEquals("LINESTART", parts[10 + 1]); + assertEquals("ALIGNEDLEFT", parts[11 + 1]); + } + + /** + * Test the compact feature extraction - verifying we extract only + * the columns specified in featuresIndices. + */ + @Test + public void testCompactFeatureExtraction() { + String line = "token a b c d e f g h i BLOCKSTART LINESTART ALIGNEDLEFT m n o p q r s t u v w x y z"; + String[] parts = line.split("[\\t\\s]+"); + + // featuresIndices = [9, 10, 11] (select columns 9, 10, 11 from Python's + // features array) + java.util.List featuresIndices = java.util.Arrays.asList(9, 10, 11); + + // Extract features using the +1 offset + String[] extractedFeatures = new String[featuresIndices.size()]; + for (int k = 0; k < featuresIndices.size(); k++) { + int featureIndex = featuresIndices.get(k); + int adjustedIndex = featureIndex + 1; + if (adjustedIndex < parts.length) { + extractedFeatures[k] = parts[adjustedIndex]; + } else { + extractedFeatures[k] = "0"; + } + } + + // Verify we got the correct values + assertEquals("BLOCKSTART", extractedFeatures[0]); + assertEquals("LINESTART", extractedFeatures[1]); + assertEquals("ALIGNEDLEFT", extractedFeatures[2]); + } + + /** + * Test that missing features (when adjustedIndex >= parts.length) default to + * "0". + */ + @Test + public void testMissingFeatures() { + String line = "token col1 col2"; // Only 3 columns + String[] parts = line.split("[\\t\\s]+"); + + java.util.List featuresIndices = java.util.Arrays.asList(9, 10, 11); + + String[] extractedFeatures = new String[featuresIndices.size()]; + for (int k = 0; k < featuresIndices.size(); k++) { + int featureIndex = featuresIndices.get(k); + int adjustedIndex = featureIndex + 1; + if (adjustedIndex < parts.length) { + extractedFeatures[k] = parts[adjustedIndex]; + } else { + extractedFeatures[k] = "0"; // Default for missing + } + } + + // All should be "0" since parts only has 3 elements + assertEquals("0", extractedFeatures[0]); + assertEquals("0", extractedFeatures[1]); + assertEquals("0", extractedFeatures[2]); + } + + // ========================================================================= + // Label Conversion Tests (delft2grobidLabel logic) + // ========================================================================= + + /** + * Test IOB "O" label converts to GROBID "O" (OTHER_LABEL). + */ + @Test + public void testLabelConversion_OLabel() { + String result = convertLabel("O"); + assertEquals("O", result); + } + + /** + * Test IOB "B-" prefix converts to GROBID "I-" prefix. + */ + @Test + public void testLabelConversion_BPrefix() { + String result = convertLabel("B-title"); + assertEquals("I-", result); + } + + /** + * Test IOB "I-" prefix converts to GROBID "<" ... ">" format. + */ + @Test + public void testLabelConversion_IPrefix() { + String result = convertLabel("I-title"); + assertEquals("<title>", result); + } + + /** + * Test <PAD> label converts to "O". + */ + @Test + public void testLabelConversion_PADLabel() { + String result = convertLabel("<PAD>"); + assertEquals("O", result); + } + + // Helper to simulate delft2grobidLabel + private String convertLabel(String label) { + if (label.equals("O") || label.trim().equals("<PAD>")) { + return "O"; + } else if (label.startsWith("B-")) { + return label.replace("B-", "I-<") + ">"; + } else if (label.startsWith("I-")) { + return "<" + label.substring(2) + ">"; + } + return label; + } + + // ========================================================================= + // Sequence Chunking Tests + // ========================================================================= + + /** + * Test chunking calculation for sequences that fit in one chunk. + */ + @Test + public void testChunking_fitsInOneChunk() { + int totalTokens = 400; + int maxSeqLength = 512; + + int numChunks = (int) Math.ceil((double) totalTokens / maxSeqLength); + + assertEquals(1, numChunks); + } + + /** + * Test chunk boundaries are calculated correctly. + */ + @Test + public void testChunkBoundaries() { + int totalTokens = 1000; + int maxSeqLength = 512; + + java.util.List<int[]> chunks = new java.util.ArrayList<>(); + int offset = 0; + while (offset < totalTokens) { + int chunkEnd = Math.min(offset + maxSeqLength, totalTokens); + chunks.add(new int[] { offset, chunkEnd }); + offset = chunkEnd; + } + + assertEquals(2, chunks.size()); + + // First chunk: [0, 512) + assertEquals(0, chunks.get(0)[0]); + assertEquals(512, chunks.get(0)[1]); + + // Second chunk: [512, 1000) + assertEquals(512, chunks.get(1)[0]); + assertEquals(1000, chunks.get(1)[1]); + } + + /** + * Test parsing input into sequences separated by empty lines. + */ + @Test + public void testParseSequences() { + String input = "token1\tfeature1\ntoken2\tfeature2\n\ntoken3\tfeature3\n"; + + java.util.List<java.util.List<String>> sequences = parseSequences(input); + + assertEquals(2, sequences.size()); + assertEquals(2, sequences.get(0).size()); // First sequence: 2 tokens + assertEquals(1, sequences.get(1).size()); // Second sequence: 1 token + } + + // Helper to parse sequences + private java.util.List<java.util.List<String>> parseSequences(String input) { + java.util.List<java.util.List<String>> sequences = new java.util.ArrayList<>(); + java.util.List<String> current = new java.util.ArrayList<>(); + + for (String line : input.split("\n", -1)) { + if (line.trim().isEmpty()) { + if (!current.isEmpty()) { + sequences.add(current); + current = new java.util.ArrayList<>(); + } + } else { + current.add(line); + } + } + if (!current.isEmpty()) { + sequences.add(current); + } + return sequences; + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessingComparisonTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessingComparisonTest.java new file mode 100644 index 0000000000..e76a4d0279 --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessingComparisonTest.java @@ -0,0 +1,159 @@ +package org.grobid.core.engines.tagging.delft; + +import com.google.gson.Gson; +import com.google.gson.GsonBuilder; +import org.junit.BeforeClass; +import org.junit.Test; + +import java.io.*; +import java.nio.file.*; +import java.util.*; + +import static org.junit.Assert.*; + +/** + * Test to compare Java preprocessing with Python preprocessing. + * + * This test loads the same input file (example.txt from delft) and + * produces preprocessing output in JSON format that can be compared + * with the Python output. + */ +public class PreprocessingComparisonTest { + + private static final String DELFT_PATH = System.getProperty("user.home") + "/development/github/delft"; + private static final String MODEL_DIR = DELFT_PATH + "/exported_models/header-BidLSTM_CRF_FEATURES.onnx"; + private static final String INPUT_FILE = DELFT_PATH + "/example.txt"; + private static final String OUTPUT_FILE = DELFT_PATH + "/java_preprocessing.json"; + + private static Preprocessor preprocessor; + + @BeforeClass + public static void setup() throws IOException { + Path vocabPath = Paths.get(MODEL_DIR, "vocab.json"); + if (!Files.exists(vocabPath)) { + System.out.println("SKIP: vocab.json not found at " + vocabPath); + return; + } + preprocessor = Preprocessor.fromJson(vocabPath); + } + + /** + * Test that generates preprocessing output for comparison with Python. + * Run with: mvn test -Dtest=PreprocessingComparisonTest#testExportPreprocessing + */ + @Test + public void testExportPreprocessing() throws IOException { + if (preprocessor == null) { + System.out.println("SKIP: Preprocessor not loaded"); + return; + } + + // Read input file + String content = Files.readString(Paths.get(INPUT_FILE)); + String[] lines = content.split("\n", -1); + + // Parse tokens and features + List<String> tokens = new ArrayList<>(); + List<String[]> tokenFeatures = new ArrayList<>(); + + for (String line : lines) { + if (line.trim().isEmpty()) + continue; + String[] parts = line.split("[\\t\\s]+"); + if (parts.length > 0) { + tokens.add(parts[0]); + tokenFeatures.add(parts); + } + } + + int limit = Math.min(50, tokens.size()); + + // Build output + Map<String, Object> output = new LinkedHashMap<>(); + + // Config + Map<String, Object> config = new LinkedHashMap<>(); + config.put("max_char", preprocessor.getMaxCharLength()); + config.put("num_features", preprocessor.getNumFeatures()); + config.put("features_indices", preprocessor.getFeaturesIndices()); + output.put("config", config); + + // Tokens + output.put("tokens", tokens.subList(0, limit)); + + // Char indices + List<long[]> charIndices = new ArrayList<>(); + for (int i = 0; i < limit; i++) { + // Create LayoutToken for this token + org.grobid.core.layout.LayoutToken lt = new org.grobid.core.layout.LayoutToken(); + lt.setText(tokens.get(i)); + List<org.grobid.core.layout.LayoutToken> tokenList = Collections.singletonList(lt); + + // Get char indices (returned as [seq][char], we only have 1 token so take [0]) + long[][] indices = preprocessor.tokensToCharIndices(tokenList, 1); + charIndices.add(indices[0]); + } + output.put("char_indices", charIndices); + + // Feature indices + if (preprocessor.hasFeatures() && preprocessor.getFeaturesIndices() != null) { + List<Integer> featuresIndices = preprocessor.getFeaturesIndices(); + List<List<Map<String, Object>>> featureOutput = new ArrayList<>(); + + for (int i = 0; i < limit; i++) { + String[] parts = tokenFeatures.get(i); + List<Map<String, Object>> tokenFeatList = new ArrayList<>(); + + // Build feature array for tokensToFeatureIndices + String[][] singleTokenFeatures = new String[1][featuresIndices.size()]; + + for (int j = 0; j < featuresIndices.size(); j++) { + int featureColumn = featuresIndices.get(j); + // Match the fix: use featureColumn + 1 since Python's features = pieces[1:] + int adjustedColumn = featureColumn + 1; + String featureValue = adjustedColumn < parts.length ? parts[adjustedColumn] : null; + singleTokenFeatures[0][j] = featureValue; + } + + // Get mapped indices + long[][] mappedIndices = preprocessor.tokensToFeatureIndices(singleTokenFeatures, 1); + + for (int j = 0; j < featuresIndices.size(); j++) { + int featureColumn = featuresIndices.get(j); + String featureValue = singleTokenFeatures[0][j]; + long mappedIndex = mappedIndices != null ? mappedIndices[0][j] : 0; + + Map<String, Object> featInfo = new LinkedHashMap<>(); + featInfo.put("featureColumn", featureColumn); + featInfo.put("featureValue", featureValue); + featInfo.put("mappedIndex", mappedIndex); + tokenFeatList.add(featInfo); + } + + featureOutput.add(tokenFeatList); + } + output.put("feature_indices", featureOutput); + } + + // Write output + Gson gson = new GsonBuilder().setPrettyPrinting().create(); + String json = gson.toJson(output); + Files.writeString(Paths.get(OUTPUT_FILE), json); + + System.out.println("Java preprocessing output written to: " + OUTPUT_FILE); + System.out.println("\nSample of first 5 tokens:"); + for (int i = 0; i < Math.min(5, limit); i++) { + System.out.println("\nToken " + i + ": '" + tokens.get(i) + "'"); + System.out.print(" Char indices (first 10): ["); + long[] chars = charIndices.get(i); + for (int j = 0; j < Math.min(10, chars.length); j++) { + if (j > 0) + System.out.print(", "); + System.out.print(chars[j]); + } + System.out.println("]"); + } + + assertTrue("Output file should exist", Files.exists(Paths.get(OUTPUT_FILE))); + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessorTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessorTest.java new file mode 100644 index 0000000000..4cf33a4696 --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/PreprocessorTest.java @@ -0,0 +1,247 @@ +package org.grobid.core.engines.tagging.delft; + +import org.junit.Before; +import org.junit.Test; + +import java.util.*; + +import static org.hamcrest.MatcherAssert.assertThat; +import static org.hamcrest.Matchers.*; +import static org.junit.Assert.*; + +/** + * Unit tests for Preprocessor, particularly the feature extraction logic. + * + * These tests validate that: + * 1. Feature indices map correctly to vocabulary lookups + * 2. The compact features array structure works as expected + */ +public class PreprocessorTest { + + private Preprocessor preprocessor; + + // Mock vocabulary and feature mappings + private Map<String, Integer> charVocab; + private Map<Integer, String> tagIndex; + private List<Integer> featuresIndices; + private Map<Integer, Map<String, Integer>> featuresMapToIndex; + + @Before + public void setUp() { + // Simple char vocabulary + charVocab = new HashMap<>(); + charVocab.put("<PAD>", 0); + charVocab.put("<UNK>", 1); + charVocab.put("a", 2); + charVocab.put("b", 3); + charVocab.put("c", 4); + + // Simple tag index + tagIndex = new HashMap<>(); + tagIndex.put(0, "<PAD>"); + tagIndex.put(1, "O"); + tagIndex.put(2, "B-TITLE"); + tagIndex.put(3, "I-TITLE"); + + // Feature indices matching Python's 1-based indexing (columns 9, 10, 11 in + // file) + featuresIndices = Arrays.asList(9, 10, 11); + + // Feature vocabularies for each column + featuresMapToIndex = new HashMap<>(); + + // Column 9 vocabulary (e.g., BLOCK features) + Map<String, Integer> col9Vocab = new HashMap<>(); + col9Vocab.put("BLOCKSTART", 1); + col9Vocab.put("BLOCKIN", 2); + col9Vocab.put("BLOCKEND", 3); + featuresMapToIndex.put(9, col9Vocab); + + // Column 10 vocabulary (e.g., LINE features) + Map<String, Integer> col10Vocab = new HashMap<>(); + col10Vocab.put("LINESTART", 1); + col10Vocab.put("LINEIN", 2); + col10Vocab.put("LINEEND", 3); + featuresMapToIndex.put(10, col10Vocab); + + // Column 11 vocabulary (e.g., ALIGN features) + Map<String, Integer> col11Vocab = new HashMap<>(); + col11Vocab.put("ALIGNEDLEFT", 1); + col11Vocab.put("ALIGNEDRIGHT", 2); + col11Vocab.put("CENTERED", 3); + featuresMapToIndex.put(11, col11Vocab); + + preprocessor = new Preprocessor(charVocab, tagIndex, 30, featuresIndices, featuresMapToIndex); + } + + @Test + public void testHasFeatures_returnsTrue() { + assertTrue(preprocessor.hasFeatures()); + } + + @Test + public void testGetFeaturesIndices() { + List<Integer> indices = preprocessor.getFeaturesIndices(); + assertEquals(3, indices.size()); + assertEquals(Integer.valueOf(9), indices.get(0)); + assertEquals(Integer.valueOf(10), indices.get(1)); + assertEquals(Integer.valueOf(11), indices.get(2)); + } + + @Test + public void testGetNumFeatures() { + assertEquals(3, preprocessor.getNumFeatures()); + } + + /** + * Test that tokensToFeatureIndices correctly maps feature values to vocabulary + * indices. + * + * The features array is a COMPACT structure where: + * - features[tokenIdx][0] contains the value for column featuresIndices[0] + * (column 9) + * - features[tokenIdx][1] contains the value for column featuresIndices[1] + * (column 10) + * etc. + */ + @Test + public void testTokensToFeatureIndices_mapsCorrectly() { + // Compact features array: features[token][featureSlot] + // Slot 0 = value for column 9, Slot 1 = value for column 10, Slot 2 = value for + // column 11 + String[][] features = { + { "BLOCKSTART", "LINESTART", "ALIGNEDLEFT" }, // Token 0 + { "BLOCKIN", "LINEIN", "ALIGNEDRIGHT" }, // Token 1 + }; + + long[][] result = preprocessor.tokensToFeatureIndices(features, 2); + + assertNotNull(result); + assertEquals(2, result.length); // seqLength = 2 + assertEquals(3, result[0].length); // 3 features + + // Token 0: BLOCKSTART(1), LINESTART(1), ALIGNEDLEFT(1) + assertEquals(1, result[0][0]); // BLOCKSTART -> 1 + assertEquals(1, result[0][1]); // LINESTART -> 1 + assertEquals(1, result[0][2]); // ALIGNEDLEFT -> 1 + + // Token 1: BLOCKIN(2), LINEIN(2), ALIGNEDRIGHT(2) + assertEquals(2, result[1][0]); // BLOCKIN -> 2 + assertEquals(2, result[1][1]); // LINEIN -> 2 + assertEquals(2, result[1][2]); // ALIGNEDRIGHT -> 2 + } + + @Test + public void testTokensToFeatureIndices_unknownValueMapsToZero() { + String[][] features = { + { "UNKNOWN_BLOCK", "LINESTART", "ALIGNEDLEFT" }, + }; + + long[][] result = preprocessor.tokensToFeatureIndices(features, 1); + + // Unknown value maps to 0 (default) + assertEquals(0, result[0][0]); // UNKNOWN_BLOCK -> 0 + assertEquals(1, result[0][1]); // LINESTART -> 1 + assertEquals(1, result[0][2]); // ALIGNEDLEFT -> 1 + } + + @Test + public void testTokensToFeatureIndices_nullValueMapsToZero() { + String[][] features = { + { null, "LINESTART", null }, + }; + + long[][] result = preprocessor.tokensToFeatureIndices(features, 1); + + // Null value keeps default 0 + assertEquals(0, result[0][0]); // null -> 0 + assertEquals(1, result[0][1]); // LINESTART -> 1 + assertEquals(0, result[0][2]); // null -> 0 + } + + @Test + public void testTokensToFeatureIndices_padsToSeqLength() { + String[][] features = { + { "BLOCKSTART", "LINESTART", "ALIGNEDLEFT" }, + }; + + // Request seqLength=4, but only 1 token + long[][] result = preprocessor.tokensToFeatureIndices(features, 4); + + assertEquals(4, result.length); // Padded to seqLength + + // Token 0 should have correct values + assertEquals(1, result[0][0]); + + // Tokens 1-3 should be all zeros (padding) + for (int i = 1; i < 4; i++) { + for (int j = 0; j < 3; j++) { + assertEquals(0, result[i][j]); + } + } + } + + @Test + public void testTokensToFeatureIndices_truncatesToSeqLength() { + String[][] features = { + { "BLOCKSTART", "LINESTART", "ALIGNEDLEFT" }, + { "BLOCKIN", "LINEIN", "ALIGNEDRIGHT" }, + { "BLOCKEND", "LINEEND", "CENTERED" }, + }; + + // Request seqLength=2, but 3 tokens provided + long[][] result = preprocessor.tokensToFeatureIndices(features, 2); + + assertEquals(2, result.length); // Truncated to seqLength + + // Token 0 and 1 should have correct values + assertEquals(1, result[0][0]); // BLOCKSTART + assertEquals(2, result[1][0]); // BLOCKIN + } + + @Test + public void testTokensToFeatureIndices_handlesShortFeatureArray() { + // Features array shorter than expected (missing slot 2) + String[][] features = { + { "BLOCKSTART", "LINESTART" }, // Only 2 elements, should be 3 + }; + + long[][] result = preprocessor.tokensToFeatureIndices(features, 1); + + // Should not throw, and missing feature should be 0 + assertEquals(1, result[0][0]); // BLOCKSTART + assertEquals(1, result[0][1]); // LINESTART + // Slot 2 is missing in input, should remain 0 + assertEquals(0, result[0][2]); + } + + @Test + public void testNoFeatures_returnsNull() { + // Create preprocessor without features + Preprocessor noFeaturesPreprocessor = new Preprocessor(charVocab, tagIndex, 30); + + assertFalse(noFeaturesPreprocessor.hasFeatures()); + assertNull(noFeaturesPreprocessor.tokensToFeatureIndices(new String[][] {}, 1)); + } + + @Test + public void testCreateMask() { + boolean[] mask = preprocessor.createMask(3, 5); + + assertEquals(5, mask.length); + assertTrue(mask[0]); + assertTrue(mask[1]); + assertTrue(mask[2]); + assertFalse(mask[3]); + assertFalse(mask[4]); + } + + @Test + public void testGetTagIndex() { + Map<Integer, String> tags = preprocessor.getTagIndex(); + + assertEquals("O", tags.get(1)); + assertEquals("B-TITLE", tags.get(2)); + assertEquals("I-TITLE", tags.get(3)); + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/WordEmbeddingsIntegrationTest.java b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/WordEmbeddingsIntegrationTest.java new file mode 100644 index 0000000000..c815dc7afb --- /dev/null +++ b/grobid-core/src/test/java/org/grobid/core/engines/tagging/delft/WordEmbeddingsIntegrationTest.java @@ -0,0 +1,201 @@ +package org.grobid.core.engines.tagging.delft; + +import org.grobid.core.utilities.GrobidProperties; +import org.junit.*; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; + +import static org.hamcrest.CoreMatchers.is; +import static org.hamcrest.CoreMatchers.notNullValue; +import static org.hamcrest.MatcherAssert.assertThat; +import static org.hamcrest.Matchers.greaterThan; +import static org.junit.Assert.assertTrue; +import static org.junit.Assume.assumeTrue; + +/** + * Integration test for WordEmbeddings LMDB lookup. + * + * This test verifies that ONNX word embeddings can be loaded and queried + * correctly from the LMDB database. It helps diagnose issues with: + * - LMDB native library loading (especially on Linux) + * - LMDB database format compatibility + * - Embeddings path configuration + * + * Prerequisites: + * - Embeddings must be preloaded using: python3 + * grobid-home/scripts/preload_embeddings.py --embedding glove-840B + * - The LMDB database should be at {delft}/data/db/glove-840B + */ +public class WordEmbeddingsIntegrationTest { + + private static final String EMBEDDINGS_NAME = "glove-840B"; + private static final int EMBEDDING_SIZE = 300; // GloVe-840B dimension + + private static Path embeddingsPath; + private WordEmbeddings embeddings; + + @BeforeClass + public static void setUpClass() { + // Initialize GROBID properties + GrobidProperties.getInstance(); + + // Get embeddings path + String delftPath = GrobidProperties.getDeLFTFilePath(); + embeddingsPath = Path.of(delftPath, "data", "db", EMBEDDINGS_NAME); + } + + @Before + public void setUp() throws IOException { + // Skip test if embeddings are not available + assumeTrue("Embeddings not found at " + embeddingsPath + + ". Please run: python3 grobid-home/scripts/preload_embeddings.py --embedding glove-840B", + Files.exists(embeddingsPath) && Files.isDirectory(embeddingsPath)); + + // Open embeddings database + embeddings = WordEmbeddings.getInstance(embeddingsPath, EMBEDDING_SIZE); + } + + @After + public void tearDown() { + if (embeddings != null) { + embeddings.close(); + } + } + + @Test + public void testEmbeddingsCanBeOpened() { + // If we get here without exception, the database opened successfully + assertThat(embeddings, is(notNullValue())); + assertThat(embeddings.getEmbeddingSize(), is(EMBEDDING_SIZE)); + } + + @Test + public void testLookupKnownWord() { + // "the" is one of the most common words and should be in any embedding + float[] embedding = embeddings.getEmbedding("the"); + + assertThat("Embedding should not be null", embedding, is(notNullValue())); + assertThat("Embedding should have correct dimension", embedding.length, is(EMBEDDING_SIZE)); + + // Check that the embedding is not all zeros (word was found) + double sumSquares = 0.0; + for (float f : embedding) { + sumSquares += f * f; + } + assertThat("Embedding for 'the' should not be all zeros", sumSquares, greaterThan(0.0)); + + // Validate embedding values are in expected range for GloVe + // If LMDB contains pickled numpy format (not raw float32), values will be + // garbage + validateEmbeddingValuesInRange(embedding, "the"); + } + + @Test + public void testLookupAnotherKnownWord() { + // Test another common word + float[] embedding = embeddings.getEmbedding("science"); + + assertThat(embedding, is(notNullValue())); + assertThat(embedding.length, is(EMBEDDING_SIZE)); + + // Check that the embedding is not all zeros + double sumSquares = 0.0; + for (float f : embedding) { + sumSquares += f * f; + } + assertThat("Embedding for 'science' should not be all zeros", sumSquares, greaterThan(0.0)); + } + + @Test + public void testContainsKnownWord() { + // Test the contains method for a word that should exist + assertTrue("Database should contain 'the'", embeddings.contains("the")); + assertTrue("Database should contain 'and'", embeddings.contains("and")); + } + + @Test + public void testGetMultipleEmbeddings() { + String[] words = { "the", "quick", "brown", "fox" }; + float[][] embeddingsResult = embeddings.getEmbeddings(words); + + assertThat("Batch result should have correct length", + embeddingsResult.length, is(words.length)); + + for (int i = 0; i < words.length; i++) { + assertThat("Each embedding should have correct dimension", + embeddingsResult[i].length, is(EMBEDDING_SIZE)); + } + } + + @Test + public void testDigitNormalization() { + // WordEmbeddings should normalize digits to "0" + // So "2024" should look up "0000" + float[] embedding = embeddings.getEmbedding("2024"); + + assertThat(embedding, is(notNullValue())); + assertThat(embedding.length, is(EMBEDDING_SIZE)); + // Note: The normalized form "0000" may or may not be in the vocabulary, + // but the lookup should succeed (returning zero vector if not found) + } + + @Test + public void testUnknownWordReturnsZeroVector() { + // A very unlikely word that should not be in the vocabulary + float[] embedding = embeddings.getEmbedding("xyzzy12345qwerty"); + + assertThat(embedding, is(notNullValue())); + assertThat(embedding.length, is(EMBEDDING_SIZE)); + + // Should be all zeros + double sumSquares = 0.0; + for (float f : embedding) { + sumSquares += f * f; + } + assertThat("Unknown word should return zero vector", sumSquares, is(0.0)); + } + + /** + * Validates that embedding values are in expected range for GloVe embeddings. + * + * GloVe embeddings typically have values in the range of approximately -5 to 5. + * If the LMDB database contains pickled numpy format instead of raw float32, + * the bytes will be interpreted as garbage floats with extreme values (often + * very large or NaN/Infinity). + * + * @param embedding The embedding vector to validate + * @param word The word being looked up (for error messages) + */ + private void validateEmbeddingValuesInRange(float[] embedding, String word) { + final float MAX_VALID_VALUE = 10.0f; // GloVe values are typically < 5 + + for (int i = 0; i < embedding.length; i++) { + float value = embedding[i]; + + // Check for NaN or Infinity (common when interpreting pickle bytes as float) + assertTrue( + String.format("Embedding for '%s' contains NaN at index %d. " + + "This suggests the LMDB database contains pickled numpy format " + + "instead of raw float32. Please regenerate embeddings using: " + + "python3 grobid-home/scripts/preload_embeddings.py --embedding glove-840B", + word, i), + !Float.isNaN(value)); + + assertTrue( + String.format("Embedding for '%s' contains Infinity at index %d. " + + "This suggests the LMDB database contains pickled numpy format " + + "instead of raw float32.", word, i), + !Float.isInfinite(value)); + + // Check for extreme values (pickled data often produces very large floats) + assertTrue( + String.format("Embedding for '%s' has extreme value %.2f at index %d " + + "(expected range: -%.0f to %.0f). This suggests the LMDB database " + + "contains pickled numpy format instead of raw float32.", + word, value, i, MAX_VALID_VALUE, MAX_VALID_VALUE), + Math.abs(value) <= MAX_VALID_VALUE); + } + } +} diff --git a/grobid-core/src/test/java/org/grobid/core/test/EngineTest.java b/grobid-core/src/test/java/org/grobid/core/test/EngineTest.java index ae882e3756..f8449e45d1 100755 --- a/grobid-core/src/test/java/org/grobid/core/test/EngineTest.java +++ b/grobid-core/src/test/java/org/grobid/core/test/EngineTest.java @@ -2,6 +2,7 @@ import org.grobid.core.engines.Engine; import org.grobid.core.factory.GrobidFactory; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.AfterClass; import org.junit.BeforeClass; @@ -10,6 +11,7 @@ public abstract class EngineTest { @BeforeClass public static void setUpClass() throws Exception { + TestEngineUtils.initGrobidForceWapiti(); engine = GrobidFactory.getInstance().getEngine(); } diff --git a/grobid-core/src/test/java/org/grobid/core/test/TestFullTextParser.java b/grobid-core/src/test/java/org/grobid/core/test/TestFullTextParser.java index ee1bafa44e..1ed0bbf195 100755 --- a/grobid-core/src/test/java/org/grobid/core/test/TestFullTextParser.java +++ b/grobid-core/src/test/java/org/grobid/core/test/TestFullTextParser.java @@ -11,7 +11,6 @@ import org.grobid.core.engines.label.TaggingLabel; import org.grobid.core.factory.GrobidFactory; import org.grobid.core.layout.Block; -import org.grobid.core.utilities.GrobidProperties; import org.junit.*; import java.io.File; @@ -29,10 +28,6 @@ public class TestFullTextParser extends EngineTest { - @BeforeClass - public static void init() { - GrobidProperties.getInstance(); - } @AfterClass public static void tearDown(){ diff --git a/grobid-core/src/test/java/org/grobid/core/utilities/LayoutTokensUtilIntegrationTest.java b/grobid-core/src/test/java/org/grobid/core/utilities/LayoutTokensUtilIntegrationTest.java index 94331b0e0b..81b68da092 100644 --- a/grobid-core/src/test/java/org/grobid/core/utilities/LayoutTokensUtilIntegrationTest.java +++ b/grobid-core/src/test/java/org/grobid/core/utilities/LayoutTokensUtilIntegrationTest.java @@ -4,7 +4,6 @@ import org.grobid.core.document.DocumentSource; import org.grobid.core.engines.Engine; import org.grobid.core.engines.config.GrobidAnalysisConfig; -import org.grobid.core.main.LibraryLoader; import org.junit.BeforeClass; import org.junit.Test; @@ -17,8 +16,7 @@ public class LayoutTokensUtilIntegrationTest { @BeforeClass public static void setUp() throws Exception { - LibraryLoader.load(); - GrobidProperties.getInstance(); + TestEngineUtils.initGrobidForceWapiti(); } @Test diff --git a/grobid-core/src/test/java/org/grobid/core/visualization/TestCitationsVisualizer.java b/grobid-core/src/test/java/org/grobid/core/visualization/TestCitationsVisualizer.java index 8ec44d853e..556d764b29 100644 --- a/grobid-core/src/test/java/org/grobid/core/visualization/TestCitationsVisualizer.java +++ b/grobid-core/src/test/java/org/grobid/core/visualization/TestCitationsVisualizer.java @@ -7,7 +7,9 @@ import org.grobid.core.engines.Engine; import org.grobid.core.engines.config.GrobidAnalysisConfig; import org.grobid.core.factory.GrobidFactory; +import org.grobid.core.utilities.TestEngineUtils; import org.junit.AfterClass; +import org.junit.BeforeClass; import org.junit.Test; import java.io.File; @@ -16,8 +18,6 @@ import java.util.Arrays; import java.util.List; -import com.fasterxml.jackson.core.Versioned; - import static org.junit.Assert.assertTrue; import static org.junit.Assert.assertEquals; @@ -25,6 +25,11 @@ public class TestCitationsVisualizer { static final ObjectMapper mapper = new ObjectMapper(); + @BeforeClass + public static void setUp() { + TestEngineUtils.initGrobidForceWapiti(); + } + @AfterClass public static void tearDown(){ GrobidFactory.reset(); diff --git a/grobid-core/src/test/kotlin/org/grobid/core/engines/FundingAcknowledgementParserIntegrationTest.kt b/grobid-core/src/test/kotlin/org/grobid/core/engines/FundingAcknowledgementParserIntegrationTest.kt index 4ae2422567..658314ad80 100644 --- a/grobid-core/src/test/kotlin/org/grobid/core/engines/FundingAcknowledgementParserIntegrationTest.kt +++ b/grobid-core/src/test/kotlin/org/grobid/core/engines/FundingAcknowledgementParserIntegrationTest.kt @@ -1,7 +1,7 @@ package org.grobid.core.engines import org.grobid.core.engines.config.GrobidAnalysisConfig -import org.grobid.core.factory.AbstractEngineFactory +import org.grobid.core.utilities.TestEngineUtils import org.grobid.core.utilities.GrobidConfig import org.grobid.core.utilities.GrobidProperties import org.hamcrest.MatcherAssert.assertThat @@ -10,7 +10,6 @@ import org.junit.Before import org.junit.BeforeClass import org.junit.Test import org.xmlunit.matchers.CompareMatcher -import java.util.* class FundingAcknowledgementParserIntegrationTest { @@ -267,7 +266,7 @@ class FundingAcknowledgementParserIntegrationTest { @BeforeClass @Throws(java.lang.Exception::class) fun setInitialContext(): Unit { - AbstractEngineFactory.init() + TestEngineUtils.initGrobidForceWapiti() } } } \ No newline at end of file diff --git a/grobid-home/config/grobid-onnx.yaml b/grobid-home/config/grobid-onnx.yaml new file mode 100644 index 0000000000..b170a1dce0 --- /dev/null +++ b/grobid-home/config/grobid-onnx.yaml @@ -0,0 +1,257 @@ +# this is the configuration file for the GROBID instance using ONNX models (no DeLFT/Python) +# This configuration uses ONNX for deep learning models and Wapiti for CRF models. + +grobid: + # where all the Grobid resources are stored (models, lexicon, native libraries, etc.), normally no need to change + grobidHome: "grobid-home" + + # path relative to the grobid-home path (e.g. tmp for grobid-home/tmp) or absolute path (/tmp) + temp: "tmp" + + # normally nothing to change here, path relative to the grobid-home path (e.g. grobid-home/lib) + nativelibrary: "lib" + + pdf: + pdfalto: + # path relative to the grobid-home path (e.g. grobid-home/pdfalto), you don't want to change this normally + path: "pdfalto" + # security for PDF parsing + memoryLimitMb: 6096 + timeoutSec: 120 + + # security relative to the PDF parsing result + blocksMax: 200000 + tokensMax: 1000000 + + consolidation: + # define the bibliographical data consolidation service to be used, either "crossref" for CrossRef REST API or + # "glutton" for https://github.com/kermitt2/biblio-glutton + service: "crossref" + #service: "glutton" + glutton: + #url: "https://cloud.science-miner.com/glutton" + url: "http://localhost:8080" + timeoutSec: 60 + crossref: + mailto: + # NOTE! To use the Crossref web API, you need normally to use it politely + # and to indicate an email address here, e.g. mailto: "toto@titi.tutu" + token: + # to use Crossref metadata plus service (available by subscription) + #token: "yourmysteriouscrossrefmetadataplusauthorizationtokentobeputhere" + timeoutSec: 60 + # Timeout for CrossRef API calls (in seconds) - USE with CARE! + proxy: + # proxy to be used when doing external call to the consolidation service + host: + port: + + # CORS configuration for the GROBID web API service + corsAllowedOrigins: "*" + corsAllowedMethods: "OPTIONS,GET,PUT,POST,DELETE,HEAD" + corsAllowedHeaders: "X-Requested-With,Content-Type,Accept,Origin" + + # the actual implementation for language recognition to be used + languageDetectorFactory: "org.grobid.core.lang.impl.CybozuLanguageDetectorFactory" + + # the actual implementation for optional sentence segmentation to be used (PragmaticSegmenter or OpenNLP) + #sentenceDetectorFactory: "org.grobid.core.lang.impl.PragmaticSentenceDetectorFactory" + sentenceDetectorFactory: "org.grobid.core.lang.impl.OpenNLPSentenceDetectorFactory" + + # maximum concurrency allowed to GROBID server for processing parallel requests - change it according to your CPU/GPU capacities + # for a production server running only GROBID, set the value slightly above the available number of threads of the server + # to get the best performance and security + concurrency: 10 + # when the pool is full, for queries waiting for the availability of a Grobid engine, this is the maximum time wait to try + # to get an engine (in seconds) - normally never change it + poolMaxWait: 1 + + # DeLFT is not used in this ONNX-only configuration + delft: + install: "../delft" + pythonVirtualEnv: + + wapiti: + # Wapiti global parameters + # number of threads for training the wapiti models (0 to use all available processors) + nbThreads: 0 + + models: + # ONNX-only configuration: models use either "onnx" or "wapiti" engine + # No "delft" engine is used in this configuration + + - name: "segmentation" + # at this time, must always be CRF wapiti, the input sequence size is too large for a Deep Learning implementation + engine: "wapiti" + wapiti: + epsilon: 0.0000001 + window: 50 + nbMaxIterations: 2000 + + - name: "segmentation-article-light" + engine: "wapiti" + wapiti: + epsilon: 0.0000001 + window: 50 + nbMaxIterations: 2000 + + - name: "segmentation-article-light-ref" + engine: "wapiti" + wapiti: + epsilon: 0.0000001 + window: 50 + nbMaxIterations: 2000 + + - name: "segmentation-sdo-ietf" + engine: "wapiti" + wapiti: + epsilon: 0.0000001 + window: 50 + nbMaxIterations: 2000 + + - name: "fulltext" + # at this time, must always be CRF wapiti, the input sequence size is too large for a Deep Learning implementation + engine: "wapiti" + wapiti: + epsilon: 0.0001 + window: 20 + nbMaxIterations: 1500 + + - name: "header" + engine: "onnx" + wapiti: + epsilon: 0.000001 + window: 30 + nbMaxIterations: 1500 + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "header-article-light" + engine: "wapiti" + wapiti: + epsilon: 0.000001 + window: 30 + nbMaxIterations: 1500 + + - name: "header-article-light-ref" + engine: "wapiti" + wapiti: + epsilon: 0.000001 + window: 30 + nbMaxIterations: 1500 + + - name: "header-sdo-ietf" + engine: "wapiti" + wapiti: + epsilon: 0.000001 + window: 30 + nbMaxIterations: 1500 + + - name: "reference-segmenter" + engine: "onnx" + wapiti: + epsilon: 0.00001 + window: 20 + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "name-header" + engine: "wapiti" + + - name: "name-citation" + engine: "wapiti" + + - name: "date" + engine: "wapiti" + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "figure" + engine: "wapiti" + wapiti: + epsilon: 0.00001 + window: 20 + + - name: "table" + engine: "wapiti" + wapiti: + epsilon: 0.00001 + window: 20 + + - name: "affiliation-address" + engine: "onnx" + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "citation" + engine: "onnx" + wapiti: + epsilon: 0.00001 + window: 50 + nbMaxIterations: 3000 + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "patent-citation" + engine: "wapiti" + wapiti: + epsilon: 0.0001 + window: 20 + + - name: "funding-acknowledgement" + engine: "onnx" + wapiti: + epsilon: 0.00001 + window: 50 + nbMaxIterations: 2000 + onnx: + architecture: "BidLSTM_CRF_FEATURES" + + - name: "copyright" + engine: "onnx" + delft: + architecture: "gru" + onnx: + architecture: "gru" + + - name: "license" + engine: "onnx" + delft: + architecture: "gru" + onnx: + architecture: "gru" + + # for **service only**: how to load the models, + # false -> models are loaded when needed, avoiding putting in memory useless models (only in case of CRF) but slow down + # significantly the service at first call + # true -> all the models are loaded into memory at the server startup (default), slow the start of the services + # and models not used will take some more memory (only in case of CRF), but server is immediatly warm and ready + modelPreload: true + +server: + type: custom + applicationConnectors: + - type: http + port: 8070 + adminConnectors: + - type: http + port: 8071 + registerDefaultExceptionMappers: false + # change the following for having all http requests logged + requestLog: + appenders: [] + +# these logging settings apply to the Grobid service usage mode +logging: + level: INFO + loggers: + org.apache.pdfbox.pdmodel.font.PDSimpleFont: "OFF" + org.glassfish.jersey.internal: "OFF" + com.squarespace.jersey2.guice.JerseyGuiceUtils: "OFF" + appenders: + - type: console + threshold: INFO + timeZone: UTC + # uncomment to have the logs in json format + #layout: + # type: json diff --git a/grobid-home/config/grobid.yaml b/grobid-home/config/grobid.yaml index 7228d9ae95..7182379c9a 100644 --- a/grobid-home/config/grobid.yaml +++ b/grobid-home/config/grobid.yaml @@ -139,8 +139,8 @@ grobid: nbMaxIterations: 1500 - name: "header" - engine: "wapiti" - #engine: "delft" + engine: "onnx" +# engine: "delft" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.000001 @@ -148,7 +148,7 @@ grobid: nbMaxIterations: 1500 delft: # deep learning parameters - architecture: "BidLSTM_ChainCRF_FEATURES" + architecture: "BidLSTM_CRF_FEATURES" #transformer: "allenai/scibert_scivocab_cased" useELMo: false runtime: @@ -162,6 +162,8 @@ grobid: #batch_size: 6 max_sequence_length: 3000 batch_size: 9 + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "header-article-light" engine: "wapiti" @@ -196,8 +198,9 @@ grobid: nbMaxIterations: 1500 - name: "reference-segmenter" - engine: "wapiti" - #engine: "delft" + #engine: "wapiti" +# engine: "delft" + engine: "onnx" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.00001 @@ -214,6 +217,8 @@ grobid: # parameters used for training max_sequence_length: 3000 batch_size: 10 + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "name-header" engine: "wapiti" @@ -232,9 +237,12 @@ grobid: - name: "date" engine: "wapiti" #engine: "delft" +# engine: "onnx" delft: # deep learning parameters architecture: "BidLSTM_CRF_FEATURES" + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "figure" engine: "wapiti" @@ -259,15 +267,19 @@ grobid: architecture: "BidLSTM_CRF" - name: "affiliation-address" - engine: "wapiti" +# engine: "wapiti" #engine: "delft" + engine: "onnx" delft: # deep learning parameters architecture: "BidLSTM_CRF_FEATURES" + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "citation" - engine: "wapiti" - #engine: "delft" + #engine: "wapiti" +# engine: "delft" + engine: "onnx" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.00001 @@ -287,6 +299,8 @@ grobid: # parameters used for training max_sequence_length: 500 batch_size: 50 + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "patent-citation" engine: "wapiti" @@ -309,8 +323,9 @@ grobid: batch_size: 40 - name: "funding-acknowledgement" - engine: "wapiti" +# engine: "wapiti" #engine: "delft" + engine: "onnx" wapiti: # wapiti training parameters, they will be used at training time only epsilon: 0.00001 @@ -330,28 +345,36 @@ grobid: # parameters used for training max_sequence_length: 500 batch_size: 40 + onnx: + architecture: "BidLSTM_CRF_FEATURES" - name: "copyright" # at this time, we only have a DeLFT implementation, # use "wapiti" if the deep learning library JNI is not available and model will then be ignored #engine: "delft" - engine: "wapiti" +# engine: "wapiti" + engine: "onnx" delft: # deep learning parameters architecture: "gru" #architecture: "bert" #transformer: "allenai/scibert_scivocab_cased" + onnx: + architecture: "gru" - name: "license" # at this time, for being active, it must be DeLFT, no other implementation is available # use "wapiti" if the deep learning library JNI is not available and model will then be ignored #engine: "delft" - engine: "wapiti" +# engine: "wapiti" + engine: "onnx" delft: # deep learning parameters architecture: "gru" #architecture: "bert" #transformer: "allenai/scibert_scivocab_cased" + onnx: + architecture: "gru" # for **service only**: how to load the models, # false -> models are loaded when needed, avoiding putting in memory useless models (only in case of CRF) but slow down @@ -380,6 +403,9 @@ logging: org.apache.pdfbox.pdmodel.font.PDSimpleFont: "OFF" org.glassfish.jersey.internal: "OFF" com.squarespace.jersey2.guice.JerseyGuiceUtils: "OFF" + # org.eclipse.jetty: "OFF" + # org.grobid: "INFO" + # org.grobid.core.engines.tagging.delft.WordEmbeddings: "DEBUG" appenders: - type: console threshold: INFO diff --git a/grobid-home/models/affiliation-address-BidLSTM_CRF/config.json b/grobid-home/models/affiliation-address-BidLSTM_CRF/config.json deleted file mode 100644 index ea73141bf9..0000000000 --- a/grobid-home/models/affiliation-address-BidLSTM_CRF/config.json +++ /dev/null @@ -1,26 +0,0 @@ -{ - "model_name": "affiliation-address-BidLSTM_CRF", - "architecture": "BidLSTM_CRF", - "embeddings_name": "glove-840B", - "char_vocab_size": 152, - "case_vocab_size": 8, - "char_embedding_size": 25, - "num_char_lstm_units": 25, - "max_char_length": 30, - "features_vocabulary_size": 12, - "features_indices": null, - "features_embedding_size": 4, - "features_lstm_units": 4, - "max_sequence_length": 600, - "word_embedding_size": 300, - "num_word_lstm_units": 100, - "case_embedding_size": 5, - "dropout": 0.5, - "recurrent_dropout": 0.5, - "use_crf": true, - "use_chain_crf": false, - "fold_number": 1, - "batch_size": 20, - "transformer_name": null, - "use_ELMo": false -} \ No newline at end of file diff --git a/grobid-home/models/affiliation-address-BidLSTM_CRF/model_weights.hdf5 b/grobid-home/models/affiliation-address-BidLSTM_CRF/model_weights.hdf5 deleted file mode 100644 index 8775d3492c..0000000000 Binary files a/grobid-home/models/affiliation-address-BidLSTM_CRF/model_weights.hdf5 and /dev/null differ diff --git a/grobid-home/models/affiliation-address-BidLSTM_CRF/preprocessor.json b/grobid-home/models/affiliation-address-BidLSTM_CRF/preprocessor.json deleted file mode 100644 index ac8c8629be..0000000000 --- a/grobid-home/models/affiliation-address-BidLSTM_CRF/preprocessor.json +++ /dev/null @@ -1,223 +0,0 @@ -{ - "padding": true, - "return_lengths": true, - "return_word_embeddings": true, - "return_casing": false, - "return_features": false, - "return_chars": true, - "return_bert_embeddings": false, - "vocab_char": { - "<PAD>": 0, - "<UNK>": 1, - "!": 2, - "\"": 3, - "#": 4, - "$": 5, - "&": 6, - "'": 7, - "(": 8, - ")": 9, - "*": 10, - "+": 11, - ",": 12, - "-": 13, - ".": 14, - "/": 15, - "0": 16, - "1": 17, - "2": 18, - "3": 19, - "4": 20, - "5": 21, - "6": 22, - "7": 23, - "8": 24, - "9": 25, - ":": 26, - ";": 27, - ">": 28, - "@": 29, - "A": 30, - "B": 31, - "C": 32, - "D": 33, - "E": 34, - "F": 35, - "G": 36, - "H": 37, - "I": 38, - "J": 39, - "K": 40, - "L": 41, - "M": 42, - "N": 43, - "O": 44, - "P": 45, - "Q": 46, - "R": 47, - "S": 48, - "T": 49, - "U": 50, - "V": 51, - "W": 52, - "X": 53, - "Y": 54, - "Z": 55, - "[": 56, - "\\": 57, - "]": 58, - "^": 59, - "_": 60, - "a": 61, - "b": 62, - "c": 63, - "d": 64, - "e": 65, - "f": 66, - "g": 67, - "h": 68, - "i": 69, - "j": 70, - "k": 71, - "l": 72, - "m": 73, - "n": 74, - "o": 75, - "p": 76, - "q": 77, - "r": 78, - "s": 79, - "t": 80, - "u": 81, - "v": 82, - "w": 83, - "x": 84, - "y": 85, - "z": 86, - "~": 87, - "\u007f": 88, - "\u0080": 89, - "\u009f": 90, - "\u00a3": 91, - "\u00a7": 92, - "\u00a8": 93, - "\u00aa": 94, - "\u00b3": 95, - "\u00b4": 96, - "\u00b6": 97, - "\u00bb": 98, - "\u00c2": 99, - "\u00c3": 100, - "\u00c5": 101, - "\u00c8": 102, - "\u00c9": 103, - "\u00cc": 104, - "\u00d5": 105, - "\u00d6": 106, - "\u00dc": 107, - "\u00df": 108, - "\u00e0": 109, - "\u00e1": 110, - "\u00e2": 111, - "\u00e3": 112, - "\u00e4": 113, - "\u00e5": 114, - "\u00e7": 115, - "\u00e8": 116, - "\u00e9": 117, - "\u00ea": 118, - "\u00ec": 119, - "\u00ed": 120, - "\u00ee": 121, - "\u00ef": 122, - "\u00f1": 123, - "\u00f2": 124, - "\u00f3": 125, - "\u00f4": 126, - "\u00f6": 127, - "\u00f8": 128, - "\u00fb": 129, - "\u00fc": 130, - "\u010d": 131, - "\u0131": 132, - "\u0141": 133, - "\u0142": 134, - "\u0144": 135, - "\u0158": 136, - "\u0160": 137, - "\u0161": 138, - "\u017a": 139, - "\u017c": 140, - "\u017e": 141, - "\u0288": 142, - "\u02d8": 143, - "\u02db": 144, - "\u2013": 145, - "\u2019": 146, - "\u2020": 147, - "\u2021": 148, - "\u22a5": 149, - "\u2424": 150, - "\uff0d": 151 - }, - "vocab_tag": { - "<PAD>": 0, - "B-<addrLine>": 1, - "B-<country>": 2, - "B-<department>": 3, - "B-<institution>": 4, - "B-<laboratory>": 5, - "B-<marker>": 6, - "B-<postBox>": 7, - "B-<postCode>": 8, - "B-<region>": 9, - "B-<settlement>": 10, - "I-<addrLine>": 11, - "I-<country>": 12, - "I-<department>": 13, - "I-<institution>": 14, - "I-<laboratory>": 15, - "I-<marker>": 16, - "I-<postBox>": 17, - "I-<postCode>": 18, - "I-<region>": 19, - "I-<settlement>": 20, - "O": 21 - }, - "vocab_case": [ - "<PAD>", - "numeric", - "allLower", - "allUpper", - "initialUpper", - "other", - "mainly_numeric", - "contains_digit" - ], - "max_char_length": 30, - "feature_preprocessor": null, - "indice_tag": { - "0": "<PAD>", - "1": "B-<addrLine>", - "2": "B-<country>", - "3": "B-<department>", - "4": "B-<institution>", - "5": "B-<laboratory>", - "6": "B-<marker>", - "7": "B-<postBox>", - "8": "B-<postCode>", - "9": "B-<region>", - "10": "B-<settlement>", - "11": "I-<addrLine>", - "12": "I-<country>", - "13": "I-<department>", - "14": "I-<institution>", - "15": "I-<laboratory>", - "16": "I-<marker>", - "17": "I-<postBox>", - "18": "I-<postCode>", - "19": "I-<region>", - "20": "I-<settlement>", - "21": "O" - } -} \ No newline at end of file diff --git a/grobid-home/models/affiliation-address-BidLSTM_CRF_FEATURES.onnx/config.json b/grobid-home/models/affiliation-address-BidLSTM_CRF_FEATURES.onnx/config.json new file 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- "return_bert_embeddings": false, - "vocab_char": { - "<PAD>": 0, - "<UNK>": 1, - "\"": 2, - "#": 3, - "%": 4, - "&": 5, - "'": 6, - "(": 7, - ")": 8, - "*": 9, - "+": 10, - ",": 11, - "-": 12, - ".": 13, - "/": 14, - "0": 15, - "1": 16, - "2": 17, - "3": 18, - "4": 19, - "5": 20, - "6": 21, - "7": 22, - "8": 23, - "9": 24, - ":": 25, - ";": 26, - "<": 27, - "=": 28, - "?": 29, - "A": 30, - "B": 31, - "C": 32, - "D": 33, - "E": 34, - "F": 35, - "G": 36, - "H": 37, - "I": 38, - "J": 39, - "K": 40, - "L": 41, - "M": 42, - "N": 43, - "O": 44, - "P": 45, - "Q": 46, - "R": 47, - "S": 48, - "T": 49, - "U": 50, - "V": 51, - "W": 52, - "X": 53, - "Y": 54, - "Z": 55, - "[": 56, - "]": 57, - "a": 58, - "b": 59, - "c": 60, - "d": 61, - "e": 62, - "f": 63, - "g": 64, - "h": 65, - "i": 66, - "j": 67, - "k": 68, - "l": 69, - "m": 70, - "n": 71, - "o": 72, - "p": 73, - "q": 74, - "r": 75, - "s": 76, - "t": 77, - "u": 78, - "v": 79, - "w": 80, - "x": 81, - "y": 82, - "z": 83, - "|": 84, - "\u00a7": 85, - "\u00b1": 86, - "\u00b7": 87, - "\u00bc": 88, - "\u00c0": 89, - "\u00d7": 90, - "\u00e1": 91, - "\u00ea": 92, - "\u00ee": 93, - "\u00f4": 94, - "\u03b5": 95, - "\u03bb": 96, - "\u03c7": 97, - "\u2020": 98, - "\u2030": 99, - "\u20ac": 100, - "\u21b5": 101, - "\u2212": 102, - "\uf0ae": 103 - }, - "vocab_tag": { - "<PAD>": 0, - "B-<content>": 1, - "B-<figDesc>": 2, - "B-<figure_head>": 3, - "B-<label>": 4, - "B-<note>": 5, - "I-<content>": 6, - "I-<figDesc>": 7, - "I-<figure_head>": 8, - "I-<note>": 9, - "O": 10 - }, - "vocab_case": [ - "<PAD>", - "numeric", - "allLower", - "allUpper", - "initialUpper", - "other", - "mainly_numeric", - "contains_digit" - ], - "max_char_length": 30, - "feature_preprocessor": null, - "indice_tag": { - "0": "<PAD>", - "1": "B-<content>", - "2": "B-<figDesc>", - "3": "B-<figure_head>", - "4": "B-<label>", - "5": "B-<note>", - "6": "I-<content>", - "7": "I-<figDesc>", - "8": "I-<figure_head>", - "9": "I-<note>", - "10": "O" - } -} \ No newline at end of file diff --git a/grobid-home/scripts/preload_embeddings.py b/grobid-home/scripts/preload_embeddings.py index 3d90ad31da..87c07a40ae 100644 --- a/grobid-home/scripts/preload_embeddings.py +++ b/grobid-home/scripts/preload_embeddings.py @@ -11,7 +11,9 @@ remove the embedding file. Obviously it will add a few GB more to the docker image. Without pre-loading, the embedding file will be -downloaded and loaded in lmdb at each run of the docker container. +downloaded and loaded in lmdb at each run of the docker container. + +Embeddings are stored as raw float32 bytes (little-endian) for direct use by Java ONNX inference. ''' import os @@ -20,10 +22,19 @@ from delft.utilities.Utilities import download_file import lmdb import json +import struct -map_size = 100 * 1024 * 1024 * 1024 +map_size = 100 * 1024 * 1024 * 1024 def preload(embeddings_name, input_path=None, registry_path=None): + """ + Preload embeddings into LMDB database as raw float32 bytes. + + Args: + embeddings_name: Name of the embeddings (e.g., 'glove-840B') + input_path: Optional path to embeddings file + registry_path: Optional path to embedding registry JSON + """ resource_registry = None if registry_path != None: with open(registry_path, 'r') as f: @@ -33,7 +44,8 @@ def preload(embeddings_name, input_path=None, registry_path=None): description = embeddings.get_description(embeddings_name) if description is None: - print("Error: embedding name", embeddings_name, "is not registered in", path) + print("Error: embedding name", embeddings_name, "is not registered") + return if input_path is None: embeddings_path = None @@ -58,22 +70,117 @@ def preload(embeddings_name, input_path=None, registry_path=None): embeddings_path = input_path if embeddings_path == None: - print("Fail to retrive embedding file for", embeddings_name) + print("Fail to retrieve embedding file for", embeddings_name) + return + + # Load and store as raw float32 bytes for Java compatibility + load_embeddings_raw_format(embeddings, embeddings_name, embeddings_path) + embeddings.clean_downloads() + + +def load_embeddings_raw_format(embeddings, embeddings_name, embeddings_path): + """ + Load embeddings from file and store as raw float32 bytes in LMDB. + + This format is compatible with Java's WordEmbeddings class which expects + little-endian float32 arrays without pickle serialization. + """ + print(f"Loading embeddings from {embeddings_path} in raw float32 format...") embedding_file = open_embedding_file(embeddings_path) if embedding_file is None: print("Error: could not open embeddings file", embeddings_path) return - # create and load the database in write mode + # Create LMDB environment embedding_lmdb_path = embeddings.registry["embedding-lmdb-path"] if not os.path.isdir(embedding_lmdb_path): os.makedirs(embedding_lmdb_path) - envFilePath = os.path.join(embedding_lmdb_path, embeddings_name) - embeddings.env = lmdb.open(envFilePath, map_size=map_size) - embeddings.load_embeddings_from_file(embeddings_path) - embeddings.clean_downloads() + env_path = os.path.join(embedding_lmdb_path, embeddings_name) + env = lmdb.open(env_path, map_size=map_size) + + max_key_size = env.max_key_size() # Get the max key size for this LMDB instance + + count = 0 + skipped = 0 + batch_size = 10000 + batch = [] + + # Read header line for some formats (e.g., word2vec binary) + first_line = True + embedding_dim = None + + for line in embedding_file: + try: + if isinstance(line, bytes): + line = line.decode('utf-8', errors='ignore') + + line = line.rstrip() + if not line: + continue + + parts = line.split(' ') + if len(parts) < 10: # Skip header or malformed lines + if first_line: + first_line = False + continue + continue + + first_line = False + word = parts[0] + + # Parse vector values + try: + values = [float(x) for x in parts[1:] if x] + except ValueError: + continue + + if embedding_dim is None: + embedding_dim = len(values) + print(f"Detected embedding dimension: {embedding_dim}") + + if len(values) != embedding_dim: + continue + + # Check key size before storing (LMDB has a max key size, typically 511 bytes) + key = word.encode('utf-8') + if len(key) >= max_key_size: + skipped += 1 + continue + + # Convert to raw float32 bytes (little-endian) + raw_bytes = struct.pack(f'<{len(values)}f', *values) + + batch.append((key, raw_bytes)) + count += 1 + + if len(batch) >= batch_size: + with env.begin(write=True) as txn: + for k, v in batch: + txn.put(k, v) + batch = [] + if count % 100000 == 0: + print(f"Processed {count} embeddings...") + + except Exception as e: + print(f"Error processing line: {e}") + continue + + # Write remaining batch + if batch: + with env.begin(write=True) as txn: + for k, v in batch: + txn.put(k, v) + + embedding_file.close() + env.close() + + print(f"Loaded {count} embeddings with dimension {embedding_dim}") + if skipped > 0: + print(f"Skipped {skipped} entries with keys exceeding max key size ({max_key_size} bytes)") + print(f"Stored in raw float32 format at: {env_path}") + if __name__ == "__main__": parser = argparse.ArgumentParser(description = "preload embeddings during the GROBID docker image build as embedded lmdb") @@ -86,7 +193,7 @@ def preload(embeddings_name, input_path=None, registry_path=None): ) parser.add_argument("--input", help="path to the embeddings file to be loaded located on the host machine (where the docker image is built)," " this is optional, without this parameter the embeddings file will be downloaded from the url indicated" - " in the embddings registry, embedding-registry.json") + " in the embeddings registry, embedding-registry.json") parser.add_argument("--registry", help="path to the embedding registry to be considered for setting the paths/urls to embeddings") args = parser.parse_args() diff --git a/grobid-home/scripts/preload_embeddings_standalone.py b/grobid-home/scripts/preload_embeddings_standalone.py new file mode 100644 index 0000000000..b1e5c70b40 --- /dev/null +++ b/grobid-home/scripts/preload_embeddings_standalone.py @@ -0,0 +1,282 @@ +''' +Standalone script to preload embeddings for GROBID ONNX Docker image. +This version has no DeLFT dependency - uses only standard library + lmdb + requests. + +Embeddings are stored as raw float32 bytes (little-endian) for direct use by Java ONNX inference. +''' + +import os +import argparse +import json +import struct +import gzip +import zipfile +import tempfile +import shutil + +try: + import lmdb +except ImportError: + print("Error: lmdb package is required. Install with: pip install lmdb") + exit(1) + +try: + import requests +except ImportError: + print("Error: requests package is required. Install with: pip install requests") + exit(1) + +map_size = 100 * 1024 * 1024 * 1024 # 100GB max size + + +def download_file(url, download_path): + """Download a file from URL to the specified path.""" + local_filename = os.path.join(download_path, url.split('/')[-1]) + + print(f"Downloading {url}...") + with requests.get(url, stream=True) as r: + r.raise_for_status() + total_size = int(r.headers.get('content-length', 0)) + downloaded = 0 + with open(local_filename, 'wb') as f: + for chunk in r.iter_content(chunk_size=8192): + f.write(chunk) + downloaded += len(chunk) + if total_size > 0: + pct = (downloaded / total_size) * 100 + print(f"\rDownloaded {downloaded / (1024*1024):.1f}MB / {total_size / (1024*1024):.1f}MB ({pct:.1f}%)", end='', flush=True) + print() + return local_filename + + +def extract_file(filepath): + """Extract a compressed file and return the path to the extracted content.""" + extract_dir = tempfile.mkdtemp() + + if filepath.endswith('.zip'): + print(f"Extracting {filepath}...") + with zipfile.ZipFile(filepath, 'r') as zf: + zf.extractall(extract_dir) + # Find the .txt or .vec file in the extracted contents + for root, dirs, files in os.walk(extract_dir): + for f in files: + if f.endswith(('.txt', '.vec')): + return os.path.join(root, f), extract_dir + elif filepath.endswith('.gz') and not filepath.endswith('.tar.gz'): + print(f"Extracting {filepath}...") + output_path = os.path.join(extract_dir, os.path.basename(filepath)[:-3]) + with gzip.open(filepath, 'rb') as f_in: + with open(output_path, 'wb') as f_out: + shutil.copyfileobj(f_in, f_out) + return output_path, extract_dir + + return filepath, None + + +def open_embedding_file(filepath): + """Open an embedding file, handling gzip compression.""" + if filepath.endswith('.gz'): + return gzip.open(filepath, 'rt', encoding='utf-8', errors='ignore') + else: + return open(filepath, 'r', encoding='utf-8', errors='ignore') + + +def preload(embeddings_name, input_path=None, registry_path=None): + """ + Preload embeddings into LMDB database as raw float32 bytes. + + Args: + embeddings_name: Name of the embeddings (e.g., 'glove-840B') + input_path: Optional path to embeddings file + registry_path: Optional path to embedding registry JSON + """ + # Load registry + registry = None + if registry_path and os.path.exists(registry_path): + with open(registry_path, 'r') as f: + registry = json.load(f) + + if registry is None: + print("Error: registry file is required") + return + + # Find embedding description + description = None + for emb in registry.get('embeddings', []): + if emb.get('name') == embeddings_name: + description = emb + break + + if description is None: + print(f"Error: embedding name '{embeddings_name}' is not registered") + return + + embeddings_path = input_path + temp_dir = None + downloaded_file = None + + if embeddings_path is None: + # Download if url is available + url = description.get('url', '') + if url: + download_path = registry.get('embedding-download-path', 'data/download') + if not os.path.isdir(download_path): + os.makedirs(download_path) + + print(f"Downloading resource file for {embeddings_name}...") + downloaded_file = download_file(url, download_path) + + if downloaded_file and os.path.isfile(downloaded_file): + print(f"Download successful: {downloaded_file}") + # Extract if compressed + embeddings_path, temp_dir = extract_file(downloaded_file) + else: + print(f"Failed to download embedding file") + return + else: + print(f"Embeddings resource URL is not specified for: {embeddings_name}") + return + + if embeddings_path is None or not os.path.exists(embeddings_path): + print(f"Fail to retrieve embedding file for {embeddings_name}") + return + + # Load and store as raw float32 bytes for Java compatibility + load_embeddings_raw_format(registry, embeddings_name, embeddings_path) + + # Cleanup + if temp_dir and os.path.exists(temp_dir): + shutil.rmtree(temp_dir) + if downloaded_file and os.path.exists(downloaded_file): + os.remove(downloaded_file) + + +def load_embeddings_raw_format(registry, embeddings_name, embeddings_path): + """ + Load embeddings from file and store as raw float32 bytes in LMDB. + + This format is compatible with Java's WordEmbeddings class which expects + little-endian float32 arrays without pickle serialization. + """ + print(f"Loading embeddings from {embeddings_path} in raw float32 format...") + + embedding_file = open_embedding_file(embeddings_path) + if embedding_file is None: + print("Error: could not open embeddings file", embeddings_path) + return + + # Create LMDB environment + embedding_lmdb_path = registry.get("embedding-lmdb-path", "data/db") + if not os.path.isdir(embedding_lmdb_path): + os.makedirs(embedding_lmdb_path) + + env_path = os.path.join(embedding_lmdb_path, embeddings_name) + env = lmdb.open(env_path, map_size=map_size) + + max_key_size = env.max_key_size() # Get the max key size for this LMDB instance + + count = 0 + skipped = 0 + batch_size = 10000 + batch = [] + + # Read header line for some formats (e.g., word2vec binary) + first_line = True + embedding_dim = None + + for line in embedding_file: + try: + if isinstance(line, bytes): + line = line.decode('utf-8', errors='ignore') + + line = line.rstrip() + if not line: + continue + + parts = line.split(' ') + if len(parts) < 10: # Skip header or malformed lines + if first_line: + first_line = False + continue + continue + + first_line = False + word = parts[0] + + # Parse vector values + try: + values = [float(x) for x in parts[1:] if x] + except ValueError: + continue + + if embedding_dim is None: + embedding_dim = len(values) + print(f"Detected embedding dimension: {embedding_dim}") + + if len(values) != embedding_dim: + continue + + # Check key size before storing (LMDB has a max key size, typically 511 bytes) + key = word.encode('utf-8') + if len(key) >= max_key_size: + skipped += 1 + continue + + # Convert to raw float32 bytes (little-endian) + raw_bytes = struct.pack(f'<{len(values)}f', *values) + + batch.append((key, raw_bytes)) + count += 1 + + if len(batch) >= batch_size: + with env.begin(write=True) as txn: + for k, v in batch: + txn.put(k, v) + batch = [] + if count % 100000 == 0: + print(f"Processed {count} embeddings...") + + except Exception as e: + print(f"Error processing line: {e}") + continue + + # Write remaining batch + if batch: + with env.begin(write=True) as txn: + for k, v in batch: + txn.put(k, v) + + embedding_file.close() + env.close() + + print(f"Loaded {count} embeddings with dimension {embedding_dim}") + if skipped > 0: + print(f"Skipped {skipped} entries with keys exceeding max key size ({max_key_size} bytes)") + print(f"Stored in raw float32 format at: {env_path}") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Standalone preload embeddings for GROBID ONNX docker image (no DeLFT dependency)" + ) + parser.add_argument("--embedding", default='glove-840B', + help=( + "the desired pre-trained word embeddings using their descriptions in the file" + " resources-registry.json," + " be sure to use here the same name as in the registry (e.g. 'glove-840B', 'fasttext-crawl', 'word2vec')" + ) + ) + parser.add_argument("--input", + help="path to the embeddings file to be loaded located on the host machine (where the docker image is built)," + " this is optional, without this parameter the embeddings file will be downloaded from the url indicated" + " in the embeddings registry") + parser.add_argument("--registry", required=True, + help="path to the embedding registry JSON file (resources-registry.json)") + + args = parser.parse_args() + + embeddings_name = args.embedding + input_path = args.input + registry_path = args.registry + + preload(embeddings_name, input_path, registry_path) diff --git a/grobid-service/src/test/java/org/grobid/service/tests/GrobidRestServiceTest.java b/grobid-service/src/test/java/org/grobid/service/tests/GrobidRestServiceTest.java index 4ea1eef310..ac4b2270c5 100755 --- a/grobid-service/src/test/java/org/grobid/service/tests/GrobidRestServiceTest.java +++ b/grobid-service/src/test/java/org/grobid/service/tests/GrobidRestServiceTest.java @@ -25,6 +25,7 @@ import org.glassfish.jersey.media.multipart.MultiPartFeature; import org.glassfish.jersey.media.multipart.file.FileDataBodyPart; import org.grobid.core.utilities.GrobidProperties; +import org.grobid.core.utilities.TestEngineUtils; import org.grobid.service.GrobidPaths; import org.grobid.service.GrobidRestService; import org.grobid.service.GrobidServiceConfiguration; @@ -56,6 +57,7 @@ public class GrobidRestServiceTest { @BeforeClass public static void setInitialContext() throws Exception { + TestEngineUtils.initGrobidForceWapiti(); } @AfterClass