Package

com.johnsnowlabs.nlp.annotators

re

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package re

Visibility
  1. Public
  2. All

Type Members

  1. case class BertREConfig(sentenceStartTokenId: Int = 102, sentenceEndTokenId: Int = 103, entity1StartTokenId: Int = 10, entity1EndTokenId: Int = 11, entity2StartTokenId: Int = 12, entity2EndTokenId: Int = 13, entity1StartTag: String = "e1b", entity1EndTag: String = "e1e", entity2StartTag: String = "e2b", entity2EndTag: String = "e2e") extends Product with Serializable

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  2. case class DLRelationInstance(relationType: String, entity1: String, entity2: String, entity1_begin: Int, entity1_end: Int, entity2_begin: Int, entity2_end: Int, chunk1: String, chunk2: String, context: Sentence) extends Product with Serializable

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  3. class PosologyREModel extends RelationExtractionModel with HasStorageRef with ParamsAndFeaturesWritable with Licensed

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  4. class REDataEncoder extends Serializable

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  5. class RENerChunksFilter extends AnnotatorModel[RENerChunksFilter] with Licensed

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  6. trait ReadRelationExtractionDLModelTensorflowModel extends ReadTensorflowModel

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  7. trait ReadablePretrainedRelationExtractionDLModel extends ParamsAndFeaturesReadable[RelationExtractionDLModel] with HasPretrained[RelationExtractionDLModel]

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  8. class RelationExtractionApproach extends GenericClassifierApproach

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  9. class RelationExtractionDLModel extends AnnotatorModel[RelationExtractionDLModel] with WriteTensorflowModel with HasStorageRef with HasCaseSensitiveProperties with Licensed

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  10. class RelationExtractionModel extends GenericClassifierModel

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    ClassifierDL is a generic Multi-class Text Classification.

    ClassifierDL is a generic Multi-class Text Classification. ClassifierDL uses the state-of-the-art Universal Sentence Encoder as an input for text classifications. The ClassifierDL annotator uses a deep learning model (DNNs) we have built inside TensorFlow and supports up to 50 classes

    NOTE: This annotator accepts a label column of a single item in either type of String, Int, Float, or Double.

    NOTE: UniversalSentenceEncoder and SentenceEmbeddings can be used for the inputCol

    See https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/classifier/dl/ClassifierDLTestSpec.scala for further reference on how to use this API

  11. case class RelationInstance(relationType: String, entity1: String, entity2: String, entity1_begin: Int, entity1_end: Int, entity2_begin: Int, entity2_end: Int, chunk1: String, chunk2: String, vector: Array[Float], description: String) extends Product with Serializable

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