com.johnsnowlabs.nlp.annotators.disambiguation

NerDisambiguatorModel

Companion object NerDisambiguatorModel

class NerDisambiguatorModel extends AnnotatorModel[NerDisambiguatorModel] with AnnotationLogic with PoolingLogicBase with KvKnowledgeExtractor with DisambiguatorModelParams with SwitchableEmbeddingsExtractor with RocksDbReader with HasSimpleAnnotate[NerDisambiguatorModel] with CheckLicense

Instantiated / pretrained model of the NerDisambiguator. Links words of interest, such as names of persons, locations and companies, from an input text document to a corresponding unique entity in a target Knowledge Base (KB). Words of interest are called Named Entities (NEs), mentions, or surface forms.

See also: NerDisambiguator for how to use the model

Linear Supertypes

CheckLicense, HasSimpleAnnotate[NerDisambiguatorModel], RocksDbReader, SwitchableEmbeddingsExtractor, DisambiguatorModelParams, KvKnowledgeExtractor, PoolingLogicBase, PoolingLogic, AnnotationLogic, PredictionLogic, EmbeddingsExtractor, Mappings, AnnotatorModel[NerDisambiguatorModel], CanBeLazy, RawAnnotator[NerDisambiguatorModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[NerDisambiguatorModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any

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Inherited

NerDisambiguatorModel
CheckLicense
HasSimpleAnnotate
RocksDbReader
SwitchableEmbeddingsExtractor
DisambiguatorModelParams
KvKnowledgeExtractor
PoolingLogicBase
PoolingLogic
AnnotationLogic
PredictionLogic
EmbeddingsExtractor
Mappings
AnnotatorModel
CanBeLazy
RawAnnotator
HasOutputAnnotationCol
HasInputAnnotationCols
HasOutputAnnotatorType
ParamsAndFeaturesWritable
HasFeatures
DefaultParamsWritable
MLWritable
Model
Transformer
PipelineStage
Logging
Params
Serializable
Serializable
Identifiable
AnyRef
Any

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Visibility

Public
All

Instance Constructors

new NerDisambiguatorModel()
new NerDisambiguatorModel(uid: String)
uid
a unique identifier for the instantiated AnnotatorModel

Type Members

type AnnotationContent = Seq[Row]

Attributes
protected
Definition Classes
AnnotatorModel
type AnnotatorType = String

Definition Classes
HasOutputAnnotatorType
type OptionAsSeq[T] = Seq[T]

Definition Classes
Mappings
final case class Prediction(chunk: Annotation, score2link: Map[Score, String], score2id: Map[Score, DataId], score2title: Map[Score, String], score2category: Map[Score, String]) extends Product with Serializable

Definition Classes
PredictionLogic

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
def $$[T](feature: StructFeature[T]): T

Attributes
protected
Definition Classes
HasFeatures
def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

Attributes
protected
Definition Classes
HasFeatures
def $$[T](feature: SetFeature[T]): Set[T]

Attributes
protected
Definition Classes
HasFeatures
def $$[T](feature: ArrayFeature[T]): Array[T]

Attributes
protected
Definition Classes
HasFeatures
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val EmbeddingsRef: String

Definition Classes
EmbeddingsExtractor
def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame

Attributes
protected
Definition Classes
AnnotatorModel
def afterAnnotate(dataset: DataFrame): DataFrame

Attributes
protected
Definition Classes
AnnotatorModel
def annotate(annotations: Seq[Annotation]): Seq[Annotation]

Definition Classes
AnnotationLogic
final def asInstanceOf[T0]: T0

Definition Classes
Any
def beforeAnnotate(dataset: Dataset[_]): Dataset[_]

Attributes
protected
Definition Classes
AnnotatorModel
final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit

Definition Classes
CheckLicense
def checkValidScope(scope: String): Unit

Definition Classes
CheckLicense
def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit

Definition Classes
CheckLicense
def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit

Definition Classes
CheckLicense
def chunk2idDb(): RocksDBConnection

Definition Classes
RocksDbReader
lazy val chunk2idF: (String) ⇒ Option[List[Int]]

Definition Classes
NerDisambiguatorModel → Mappings
final def clear(param: Param[_]): NerDisambiguatorModel.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
def copy(extra: ParamMap): NerDisambiguatorModel

Definition Classes
RawAnnotator → Model → Transformer → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
def dfAnnotate: UserDefinedFunction

Definition Classes
HasSimpleAnnotate
def embeddingType: String

Definition Classes
NerDisambiguatorModel → SwitchableEmbeddingsExtractor
val embeddingTypeParam: Param[String]
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)

Definition Classes
DisambiguatorModelParams
def enableApproximateMatching: Boolean

Definition Classes
NerDisambiguatorModel → PredictionLogic
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
def extraValidate(structType: StructType): Boolean

Attributes
protected
Definition Classes
RawAnnotator
def extraValidateMsg: String

Attributes
protected
Definition Classes
RawAnnotator
def extractKnowledgeFromKv(id2record: (DataId) ⇒ Option[Record], chunk2id: (Chunk) ⇒ Option[List[DataId]]): Knowledge

Definition Classes
KvKnowledgeExtractor
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
val features: ArrayBuffer[Feature[_, _, _]]

Definition Classes
HasFeatures
def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def findChunkId(chunk: String): Option[List[DataId]]

Definition Classes
RocksDbReader
def get[T](feature: StructFeature[T]): Option[T]

Attributes
protected
Definition Classes
HasFeatures
def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

Attributes
protected
Definition Classes
HasFeatures
def get[T](feature: SetFeature[T]): Option[Set[T]]

Attributes
protected
Definition Classes
HasFeatures
def get[T](feature: ArrayFeature[T]): Option[Array[T]]

Attributes
protected
Definition Classes
HasFeatures
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
def getChunk2idDb(): RocksDBConnection

Definition Classes
RocksDbReader
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@native()
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getEmbeddingType: String
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)

Definition Classes
DisambiguatorModelParams
def getId2Connection(): RocksDBConnection

Definition Classes
RocksDbReader
def getInputCols: Array[String]

Definition Classes
HasInputAnnotationCols
def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
def getLevenshteinDistanceThresholdParam: Double
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)

Definition Classes
DisambiguatorModelParams
def getNarrowWithApproximateMatching: Boolean
Whether to narrow prefix search results with levenstein distance based matching (Default: true)
Whether to narrow prefix search results with levenstein distance based matching (Default: true)

Definition Classes
DisambiguatorModelParams
def getNearMatchingGapParam: Int
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).

Definition Classes
DisambiguatorModelParams
def getNumFirstChars: Int
How many characters should be considered for initial prefix search in knowledge base
How many characters should be considered for initial prefix search in knowledge base

Definition Classes
DisambiguatorModelParams
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
final def getOutputCol: String

Definition Classes
HasOutputAnnotationCol
def getParam(paramName: String): Param[Any]

Definition Classes
Params
def getPredictionLimit: Int
Limit on amount of predictions N for topN predictions (Default: 100)
Limit on amount of predictions N for topN predictions (Default: 100)

Definition Classes
DisambiguatorModelParams
def getRecord(id: DataId): Option[Record]

Definition Classes
RocksDbReader
def getSentenceEmbedding(annotations: Seq[Annotation]): SentenceEmbeddingWithType

Definition Classes
SwitchableEmbeddingsExtractor → EmbeddingsExtractor
def getTokenSearch: Boolean
Whether to search by token or by chunk in knowledge base (Default: true)
Whether to search by token or by chunk in knowledge base (Default: true)

Definition Classes
DisambiguatorModelParams
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hasParent: Boolean

Definition Classes
Model
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@native()
lazy val id2categoryF: (Int) ⇒ OptionAsSeq[String]

Definition Classes
NerDisambiguatorModel → Mappings
lazy val id2embF: (Int) ⇒ OptionAsSeq[Array[Double]]

Definition Classes
NerDisambiguatorModel → Mappings
lazy val id2linkF: (Int) ⇒ OptionAsSeq[String]

Definition Classes
NerDisambiguatorModel → Mappings
def id2recordDb: RocksDBConnection

Definition Classes
RocksDbReader
lazy val id2titleF: (Int) ⇒ OptionAsSeq[String]

Definition Classes
NerDisambiguatorModel → Mappings
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
val inputAnnotatorTypes: Array[String]
Input annotator types: CHUNK, SENTENCE_EMBEDDINGS
Input annotator types: CHUNK, SENTENCE_EMBEDDINGS

Definition Classes
NerDisambiguatorModel → HasInputAnnotationCols
final val inputCols: StringArrayParam

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
lazy val knowledge: Knowledge
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
def levenshteinDistanceThreshold: Double

Definition Classes
NerDisambiguatorModel → PredictionLogic
val levenshteinDistanceThresholdParam: DoubleParam
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)

Definition Classes
DisambiguatorModelParams
def limit: Int

Definition Classes
NerDisambiguatorModel → PredictionLogic
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def msgHelper(schema: StructType): String

Attributes
protected
Definition Classes
HasInputAnnotationCols
val narrowWithApproximateMatching: BooleanParam
Whether to narrow prefix search results with levenstein distance based matching (Default: true)
Whether to narrow prefix search results with levenstein distance based matching (Default: true)

Definition Classes
DisambiguatorModelParams
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def nearMatchingGap: Int

Definition Classes
NerDisambiguatorModel → PredictionLogic
val nearMatchingGapParam: IntParam
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).

Definition Classes
DisambiguatorModelParams
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
val numFirstChars: IntParam
How many characters should be considered for initial prefix search in knowledge base
How many characters should be considered for initial prefix search in knowledge base

Definition Classes
DisambiguatorModelParams
def onWrite(path: String, spark: SparkSession): Unit

Definition Classes
RocksDbReader → ParamsAndFeaturesWritable
val optionalInputAnnotatorTypes: Array[String]

Definition Classes
HasInputAnnotationCols
val outputAnnotatorType: AnnotatorType
Output annotator types: DISAMBIGUATION
Output annotator types: DISAMBIGUATION

Definition Classes
NerDisambiguatorModel → AnnotationLogic → HasOutputAnnotatorType
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
lazy val params: Array[Param[_]]

Definition Classes
Params
var parent: Estimator[NerDisambiguatorModel]

Definition Classes
Model
def poolEmbeddings(embeddings: Array[Array[Float]]): Array[Double]

Definition Classes
PoolingLogicBase → PoolingLogic
def predictByChunk(annotations: Seq[Annotation], numFirstChars: Int): Seq[Prediction]

Definition Classes
PredictionLogic
val predictionsLimit: IntParam
Limit on amount of predictions N for topN predictions (Default: 100)
Limit on amount of predictions N for topN predictions (Default: 100)

Definition Classes
DisambiguatorModelParams
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
def searchByToken: Boolean

Definition Classes
NerDisambiguatorModel → PredictionLogic
def set[T](feature: StructFeature[T], value: T): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: SetFeature[T], value: Set[T]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: ArrayFeature[T], value: Array[T]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
final def set(paramPair: ParamPair[_]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): NerDisambiguatorModel.this.type

Definition Classes
Params
def setDefault[T](feature: StructFeature[T], value: () ⇒ T): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
HasFeatures
final def setDefault(paramPairs: ParamPair[_]*): NerDisambiguatorModel.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): NerDisambiguatorModel.this.type

Attributes
protected[org.apache.spark.ml]
Definition Classes
Params
def setEmbeddingType(v: String): NerDisambiguatorModel.this.type
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)
Can be 'bow' for word embeddings or 'sentence' for sentences (Default: sentence)

Definition Classes
DisambiguatorModelParams
final def setInputCols(value: String*): NerDisambiguatorModel.this.type

Definition Classes
HasInputAnnotationCols
def setInputCols(value: Array[String]): NerDisambiguatorModel.this.type

Definition Classes
HasInputAnnotationCols
def setLazyAnnotator(value: Boolean): NerDisambiguatorModel.this.type

Definition Classes
CanBeLazy
def setLevenshteinDistanceThresholdParam(v: Double): NerDisambiguatorModel.this.type
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)
Levenshtein distance threshold to narrow results from prefix search (Default: 0.1)

Definition Classes
DisambiguatorModelParams
def setNarrowWithApproximateMatching(v: Boolean): NerDisambiguatorModel.this.type
Whether to narrow prefix search results with levenstein distance based matching (Default: true)
Whether to narrow prefix search results with levenstein distance based matching (Default: true)

Definition Classes
DisambiguatorModelParams
def setNearMatchingGapParam(v: Int): NerDisambiguatorModel.this.type
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).
Puts a limit on a string length (by trimming the candidate chunks) during levenshtein-distance based narrowing, len(candidate) - len(entity chunk) > nearMatchingGap (Default: 4).

Definition Classes
DisambiguatorModelParams
def setNumFirstChars(v: Int): NerDisambiguatorModel.this.type
How many characters should be considered for initial prefix search in knowledge base
How many characters should be considered for initial prefix search in knowledge base

Definition Classes
DisambiguatorModelParams
final def setOutputCol(value: String): NerDisambiguatorModel.this.type

Definition Classes
HasOutputAnnotationCol
def setParent(parent: Estimator[NerDisambiguatorModel]): NerDisambiguatorModel

Definition Classes
Model
def setPredictionLimit(v: Int): NerDisambiguatorModel.this.type
Limit on amount of predictions N for topN predictions (Default: 100)
Limit on amount of predictions N for topN predictions (Default: 100)

Definition Classes
DisambiguatorModelParams
def setTokenSearch(v: Boolean): NerDisambiguatorModel.this.type
Whether to search by token or by chunk in knowledge base (Default: true)
Whether to search by token or by chunk in knowledge base (Default: true)

Definition Classes
DisambiguatorModelParams
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
val tokenSearch: BooleanParam
Whether to search by token or by chunk in knowledge base (Default: true)
Whether to search by token or by chunk in knowledge base (Default: true)

Definition Classes
DisambiguatorModelParams
final def transform(dataset: Dataset[_]): DataFrame

Definition Classes
AnnotatorModel → Transformer
def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

Definition Classes
Transformer
Annotations
@Since( "2.0.0" )
def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

Definition Classes
Transformer
Annotations
@Since( "2.0.0" ) @varargs()
final def transformSchema(schema: StructType): StructType

Definition Classes
RawAnnotator → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
NerDisambiguatorModel → Identifiable
def validate(schema: StructType): Boolean

Attributes
protected
Definition Classes
RawAnnotator
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... ) @native()
def wrapColumnMetadata(col: Column): Column

Attributes
protected
Definition Classes
RawAnnotator
def write: MLWriter

Definition Classes
ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Packages

NerDisambiguatorModel 

Companion object NerDisambiguatorModel

class NerDisambiguatorModel extends AnnotatorModel[NerDisambiguatorModel] with AnnotationLogic with PoolingLogicBase with KvKnowledgeExtractor with DisambiguatorModelParams with SwitchableEmbeddingsExtractor with RocksDbReader with HasSimpleAnnotate[NerDisambiguatorModel] with CheckLicense

Instance Constructors

Type Members

Value Members

Inherited from CheckLicense

Inherited from HasSimpleAnnotate[NerDisambiguatorModel]

Inherited from RocksDbReader

Inherited from SwitchableEmbeddingsExtractor

Inherited from DisambiguatorModelParams

Inherited from KvKnowledgeExtractor

Inherited from PoolingLogicBase

Inherited from PoolingLogic

Inherited from AnnotationLogic

Inherited from PredictionLogic

Inherited from EmbeddingsExtractor

Inherited from Mappings

Inherited from AnnotatorModel[NerDisambiguatorModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[NerDisambiguatorModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[NerDisambiguatorModel]

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

Members

Parameter setters

Parameter getters

NerDisambiguatorModel