[BUG] join queries fail when combining metadata filters and odinson queries with exact range quantifiers

[myedibleenso]

When used in conjunction with a metadata filter (parent query), a pattern (Odinson query) with an exact range quantifier (>=2) will fail to match.

import ai.lum.odinson.test.utils.OdinsonTest

val ot = new OdinsonTest()

// metadata":[{"$type":"ai.lum.odinson.TokensField","name":"doc_id","tokens":["step-bros"]}]
// "John", "C.", "Reilly", "played", ...
val ee = ot.mkExtractorEngine("step-bros")

val pattern = "[lemma=play] >nsubj [tag=NNP]{,3}"
val mf = "doc_id == 'step-bros'"
val oq = ee.mkFilteredQuery(query = pattern, metadataFilter = mf)

val res = ee.query(oq)

// both of these unexpectedly fail
numMatches(res) == 1
existsMatchWithSpan(odinResults = res, doc = 0, start = 0, end = 3) == 1

Associated unit tests (ghp/join-query-bug branch)

• odinson/core/src/test/scala/ai/lum/odinson/events/TestEventsWithState.scala

  Lines 74 to 107 in 55e9d42

  	it should "match events referencing existing mentions when an in-memory state is used along with a metadataFilter" in {
  	val ee = extractorEngineWithSpecificState(getDocument("step-bros"), "memory")
  	val grammar = """
  	metadataFilters: doc_id == 'step-bros'
  	rules:
  	- name: person-rule
  	type: basic
  	priority: 1
  	label: Person
  	pattern: |
  	[tag=NNP]{3}
  	- name: state-based-rule
  	type: event
  	label: EventBasedPersonRule
  	priority: 2
  	pattern: |
  	trigger = [lemma=play]
  	# NOTE: ending with @Person won't work
  	arg: Person = >nsubj
  	"""
  	val extractors = ee.compileRuleString(grammar).toVector
  	val mentions = ee.extractMentions(
  	extractors = extractors,
  	allowTriggerOverlaps = false,
  	disableMatchSelector = false
  	).toVector
  	getMentionsWithLabel(mentions, "EventBasedPersonRule") should have size (1)
  	}

• odinson/core/src/test/scala/ai/lum/odinson/metadata/TestJoinQueries.scala

  Lines 22 to 35 in 55e9d42

  	it should "match simple patterns with exact range quantifiers (>=2) and a metadata filter" in {
  	// create in-memory engine w/ a single doc w/ a single sentence
  	val ee = mkExtractorEngine("step-bros")
  	// "John", "C.", "Reilly", "played" ...
  	val pattern = "[lemma=play] >nsubj [tag=NNP]{3}"
  	val mf = "doc_id == 'step-bros'"
  	val oq = ee.mkFilteredQuery(query = pattern, metadataFilter = mf)
  	val res = ee.query(oq)
  	numMatches(res) should be (1)
  	existsMatchWithSpan(odinResults = res, doc = 0, start = 0, end = 3) should be (true)
  	}