
com.johnsnowlabs.nlp.annotators.TextMatcherModel.scala Maven / Gradle / Ivy
package com.johnsnowlabs.nlp.annotators
import com.johnsnowlabs.collections.SearchTrie
import com.johnsnowlabs.nlp._
import org.apache.spark.ml.util.Identifiable
import com.johnsnowlabs.nlp.AnnotatorType._
import com.johnsnowlabs.nlp.serialization.ArrayFeature
import scala.collection.mutable.ArrayBuffer
/**
* Extracts entities out of provided phrases
* @param uid internally renquired UID to make it writable
* @@ entitiesPath: Path to file with phrases to search
* @@ insideSentences: Should Extractor search only within sentence borders?
*/
class TextMatcherModel(override val uid: String) extends AnnotatorModel[TextMatcherModel] {
override val annotatorType: AnnotatorType = ENTITY
override val requiredAnnotatorTypes: Array[AnnotatorType] = Array(TOKEN)
val parsedEntities = new ArrayFeature[Array[String]](this, "parsedEntities")
def setEntities(value: Array[Array[String]]): this.type = set(parsedEntities, value)
lazy val searchTrie = SearchTrie.apply($$(parsedEntities))
/** internal constructor for writabale annotator */
def this() = this(Identifiable.randomUID("ENTITY_EXTRACTOR"))
/**
* Searches entities and stores them in the annotation
* @param text Tokenized text to search
* @return Extracted Entities
*/
private def search(text: Seq[Annotation]): Seq[Annotation] = {
val words = text.map(t => t.result)
val result = ArrayBuffer[Annotation]()
for ((begin, end) <- searchTrie.search(words)) {
val normalizedText = (begin to end).map(i => words(i)).mkString(" ")
val annotation = Annotation(
ENTITY,
text(begin).begin,
text(end).end,
normalizedText,
Map()
)
result.append(annotation)
}
result
}
/** Defines annotator phrase matching depending on whether we are using SBD or not */
override def annotate(annotations: Seq[Annotation]): Seq[Annotation] = {
search(annotations)
}
}
object TextMatcherModel extends ParamsAndFeaturesReadable[TextMatcherModel]
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