class WordEmbeddingsModel extends AnnotatorModel[WordEmbeddingsModel] with HasSimpleAnnotate[WordEmbeddingsModel] with HasEmbeddingsProperties with HasStorageModel with ParamsAndFeaturesWritable

Word Embeddings lookup annotator that maps tokens to vectors

This is the instantiated model of WordEmbeddings.

Pretrained models can be loaded with pretrained of the companion object:

val embeddings = WordEmbeddingsModel.pretrained()
    .setInputCols("document", "token")
    .setOutputCol("embeddings")

The default model is "glove_100d", if no name is provided. For available pretrained models please see the Models Hub.

There are also two convenient functions to retrieve the embeddings coverage with respect to the transformed dataset:

  • withCoverageColumn(dataset, embeddingsCol, outputCol): Adds a custom column with word coverage stats for the embedded field: (coveredWords, totalWords, coveragePercentage). This creates a new column with statistics for each row.
val wordsCoverage = WordEmbeddingsModel.withCoverageColumn(resultDF, "embeddings", "cov_embeddings")
wordsCoverage.select("text","cov_embeddings").show(false)
+-------------------+--------------+
|text               |cov_embeddings|
+-------------------+--------------+
|This is a sentence.|[5, 5, 1.0]   |
+-------------------+--------------+
  • overallCoverage(dataset, embeddingsCol): Calculates overall word coverage for the whole data in the embedded field. This returns a single coverage object considering all rows in the field.
val wordsOverallCoverage = WordEmbeddingsModel.overallCoverage(wordsCoverage,"embeddings").percentage
1.0

For extended examples of usage, see the Spark NLP Workshop and the WordEmbeddingsTestSpec.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.embeddings.WordEmbeddingsModel
import com.johnsnowlabs.nlp.EmbeddingsFinisher
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")

val tokenizer = new Tokenizer()
  .setInputCols(Array("document"))
  .setOutputCol("token")

val embeddings = WordEmbeddingsModel.pretrained()
  .setInputCols("document", "token")
  .setOutputCol("embeddings")

val embeddingsFinisher = new EmbeddingsFinisher()
  .setInputCols("embeddings")
  .setOutputCols("finished_embeddings")
  .setOutputAsVector(true)
  .setCleanAnnotations(false)

val pipeline = new Pipeline()
  .setStages(Array(
    documentAssembler,
    tokenizer,
    embeddings,
    embeddingsFinisher
  ))

val data = Seq("This is a sentence.").toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("explode(finished_embeddings) as result").show(5, 80)
+--------------------------------------------------------------------------------+
|                                                                          result|
+--------------------------------------------------------------------------------+
|[-0.570580005645752,0.44183000922203064,0.7010200023651123,-0.417129993438720...|
|[-0.542639970779419,0.4147599935531616,1.0321999788284302,-0.4024400115013122...|
|[-0.2708599865436554,0.04400600120425224,-0.020260000601410866,-0.17395000159...|
|[0.6191999912261963,0.14650000631809235,-0.08592499792575836,-0.2629800140857...|
|[-0.3397899866104126,0.20940999686717987,0.46347999572753906,-0.6479200124740...|
+--------------------------------------------------------------------------------+
See also

SentenceEmbeddings to combine embeddings into a sentence-level representation

Annotators Main Page for a list of transformer based embeddings

Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. WordEmbeddingsModel
  2. HasStorageModel
  3. HasExcludableStorage
  4. HasStorageReader
  5. HasCaseSensitiveProperties
  6. HasStorageRef
  7. HasEmbeddingsProperties
  8. HasSimpleAnnotate
  9. AnnotatorModel
  10. CanBeLazy
  11. RawAnnotator
  12. HasOutputAnnotationCol
  13. HasInputAnnotationCols
  14. HasOutputAnnotatorType
  15. ParamsAndFeaturesWritable
  16. HasFeatures
  17. DefaultParamsWritable
  18. MLWritable
  19. Model
  20. Transformer
  21. PipelineStage
  22. Logging
  23. Params
  24. Serializable
  25. Serializable
  26. Identifiable
  27. AnyRef
  28. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new WordEmbeddingsModel()

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

  2. new WordEmbeddingsModel(uid: String)

Type Members

  1. type AnnotationContent = Seq[Row]

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    WordEmbeddingsModelAnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    Takes a document and annotations and produces new annotations of this annotator's annotation type

    Takes a document and annotations and produces new annotations of this annotator's annotation type

    annotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    any number of annotations processed for every input annotation. Not necessary one to one relationship

    Definition Classes
    WordEmbeddingsModelHasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  14. val caseSensitive: BooleanParam

    Whether to ignore case in index lookups (Default depends on model)

    Whether to ignore case in index lookups (Default depends on model)

    Definition Classes
    HasCaseSensitiveProperties
  15. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  16. final def clear(param: Param[_]): WordEmbeddingsModel.this.type
    Definition Classes
    Params
  17. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  18. def copy(extra: ParamMap): WordEmbeddingsModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  19. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  21. def createReader(database: Name, connection: RocksDBConnection): WordEmbeddingsReader
    Attributes
    protected
    Definition Classes
    WordEmbeddingsModelHasStorageReader
  22. val databases: Array[Name]
    Definition Classes
    WordEmbeddingsModelHasStorageModel
  23. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. def deserializeStorage(path: String, spark: SparkSession): Unit
    Definition Classes
    HasStorageModel
  25. def dfAnnotate: UserDefinedFunction

    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    returns

    udf function to be applied to inputCols using this annotator's annotate function as part of ML transformation

    Definition Classes
    HasSimpleAnnotate
  26. val dimension: IntParam

    Number of embedding dimensions (Default depends on model)

    Number of embedding dimensions (Default depends on model)

    Definition Classes
    HasEmbeddingsProperties
  27. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  28. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  29. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  30. def explainParams(): String
    Definition Classes
    Params
  31. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  32. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  33. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  34. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  35. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  36. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  37. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  38. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  39. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. def getCaseSensitive: Boolean

    Definition Classes
    HasCaseSensitiveProperties
  43. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  44. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getDimension: Int

    Definition Classes
    HasEmbeddingsProperties
  46. def getIncludeStorage: Boolean
    Definition Classes
    HasExcludableStorage
  47. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  48. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  49. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  50. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  51. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  52. def getReader[A](database: Name): StorageReader[A]
    Attributes
    protected
    Definition Classes
    HasStorageReader
  53. def getStorageRef: String
    Definition Classes
    HasStorageRef
  54. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  55. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  56. def hasParent: Boolean
    Definition Classes
    Model
  57. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  58. val includeStorage: BooleanParam
    Definition Classes
    HasExcludableStorage
  59. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  60. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. val inputAnnotatorTypes: Array[String]

    Input annotator type : DOCUMENT, TOKEN

    Input annotator type : DOCUMENT, TOKEN

    Definition Classes
    WordEmbeddingsModelHasInputAnnotationCols
  62. final val inputCols: StringArrayParam

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  63. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  64. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  65. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  66. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  67. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  68. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  69. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  76. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  81. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  82. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  83. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  84. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    HasStorageModelParamsAndFeaturesWritable
  85. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  86. val outputAnnotatorType: AnnotatorType

    Output annotator type : WORD_EMBEDDINGS

    Output annotator type : WORD_EMBEDDINGS

    Definition Classes
    WordEmbeddingsModelHasOutputAnnotatorType
  87. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  88. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  89. var parent: Estimator[WordEmbeddingsModel]
    Definition Classes
    Model
  90. val readCacheSize: IntParam

    Cache size for items retrieved from storage.

    Cache size for items retrieved from storage. Increase for performance but higher memory consumption

  91. val readers: Map[Name, StorageReader[_]]
    Attributes
    protected
    Definition Classes
    HasStorageReader
    Annotations
    @transient()
  92. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  93. def saveStorage(path: String, spark: SparkSession, withinStorage: Boolean = false): Unit
    Definition Classes
    HasStorageModel
  94. def serializeStorage(path: String, spark: SparkSession): Unit
    Definition Classes
    HasStorageModel
  95. def set[T](feature: StructFeature[T], value: T): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def set[T](feature: SetFeature[T], value: Set[T]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  98. def set[T](feature: ArrayFeature[T], value: Array[T]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. final def set(paramPair: ParamPair[_]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  100. final def set(param: String, value: Any): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  101. final def set[T](param: Param[T], value: T): WordEmbeddingsModel.this.type
    Definition Classes
    Params
  102. def setCaseSensitive(value: Boolean): WordEmbeddingsModel.this.type

    Definition Classes
    HasCaseSensitiveProperties
  103. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  107. final def setDefault(paramPairs: ParamPair[_]*): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  108. final def setDefault[T](param: Param[T], value: T): WordEmbeddingsModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  109. def setDimension(value: Int): WordEmbeddingsModel.this.type

    Definition Classes
    HasEmbeddingsProperties
  110. def setIncludeStorage(value: Boolean): WordEmbeddingsModel.this.type
    Definition Classes
    HasExcludableStorage
  111. final def setInputCols(value: String*): WordEmbeddingsModel.this.type
    Definition Classes
    HasInputAnnotationCols
  112. final def setInputCols(value: Array[String]): WordEmbeddingsModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  113. def setLazyAnnotator(value: Boolean): WordEmbeddingsModel.this.type
    Definition Classes
    CanBeLazy
  114. final def setOutputCol(value: String): WordEmbeddingsModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  115. def setParent(parent: Estimator[WordEmbeddingsModel]): WordEmbeddingsModel
    Definition Classes
    Model
  116. def setReadCacheSize(value: Int): WordEmbeddingsModel.this.type

    Set cache size for items retrieved from storage.

    Set cache size for items retrieved from storage. Increase for performance but higher memory consumption

  117. def setStorageRef(value: String): WordEmbeddingsModel.this.type
    Definition Classes
    HasStorageRef
  118. val storageRef: Param[String]

    Unique identifier for storage (Default: this.uid)

    Unique identifier for storage (Default: this.uid)

    Definition Classes
    HasStorageRef
  119. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  120. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  121. final def transform(dataset: Dataset[_]): DataFrame

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  122. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  123. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  124. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    RawAnnotator → PipelineStage
  125. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  126. val uid: String
    Definition Classes
    WordEmbeddingsModel → Identifiable
  127. def validate(schema: StructType): Boolean

    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
    Definition Classes
    RawAnnotator
  128. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  129. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  130. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  131. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  132. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  133. def wrapEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  134. def wrapSentenceEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  135. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from HasStorageModel

Inherited from HasExcludableStorage

Inherited from HasStorageReader

Inherited from HasStorageRef

Inherited from HasEmbeddingsProperties

Inherited from CanBeLazy

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[WordEmbeddingsModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters