class NerQuestionGenerator extends AnnotatorModel[NerQuestionGenerator] with HasSimpleAnnotate[NerQuestionGenerator] with CheckLicense
Automatically generates questions for NER.
This annotator takes a NER chunk (obtained by, e.g., NerConverterInternal
) and
generates a questions based on two entity types, a pronoun and a strategy.
The question is generated in the form of [QUESTIONPRONOUN] [ENTITY1] [ENTITY2] [QUESTIONMARK].
The generated question can be used by QuestionAnswerer
annotator
to find answers to the generated questions.
Pretrained models can be loaded with pretrained
of the companion object:
val medQA = NerQuestionGenerator.pretrained() .setInputCols("ner_chunk") .setOutputCol("question")
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def
_transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
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def
afterAnnotate(dataset: DataFrame): DataFrame
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def
annotate(annotations: Seq[Annotation]): Seq[Annotation]
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final
def
asInstanceOf[T0]: T0
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def
beforeAnnotate(dataset: Dataset[_]): Dataset[_]
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final
def
checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
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- HasInputAnnotationCols
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def
checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
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def
checkValidScope(scope: String): Unit
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def
checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
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def
checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
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final
def
clear(param: Param[_]): NerQuestionGenerator.this.type
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def
clone(): AnyRef
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def
copy(extra: ParamMap): NerQuestionGenerator
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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def
defaultCopy[T <: Params](extra: ParamMap): T
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def
dfAnnotate: UserDefinedFunction
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val
entities1: StringArrayParam
List with the entity types of entities that appear first in the question.
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val
entities2: StringArrayParam
List with the entity types of entities that appear second in the question.
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
explainParam(param: Param[_]): String
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explainParams(): String
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extraValidate(structType: StructType): Boolean
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extraValidateMsg: String
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extractParamMap(): ParamMap
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extractParamMap(extra: ParamMap): ParamMap
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features: ArrayBuffer[Feature[_, _, _]]
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getClass(): Class[_]
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def
getDefault[T](param: Param[T]): Option[T]
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def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
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def
getLazyAnnotator: Boolean
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getOrDefault[T](param: Param[T]): T
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def
getOutputCol: String
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getParam(paramName: String): Param[Any]
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hasDefault[T](param: Param[T]): Boolean
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hasParent: Boolean
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initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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initializeLogIfNecessary(isInterpreter: Boolean): Unit
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val
inputAnnotatorTypes: Array[String]
Input annotator type : CHUNK
Input annotator type : CHUNK
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- NerQuestionGenerator → HasInputAnnotationCols
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final
val
inputCols: StringArrayParam
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isTraceEnabled(): Boolean
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lazyAnnotator: BooleanParam
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def
log: Logger
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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logDebug(msg: ⇒ String): Unit
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logError(msg: ⇒ String, throwable: Throwable): Unit
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logError(msg: ⇒ String): Unit
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logInfo(msg: ⇒ String, throwable: Throwable): Unit
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logName: String
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logTrace(msg: ⇒ String, throwable: Throwable): Unit
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logWarning(msg: ⇒ String, throwable: Throwable): Unit
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logWarning(msg: ⇒ String): Unit
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msgHelper(schema: StructType): String
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def
onWrite(path: String, spark: SparkSession): Unit
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val
optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
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val
outputAnnotatorType: AnnotatorType
Output annotator type : DOCUMENT
Output annotator type : DOCUMENT
- Definition Classes
- NerQuestionGenerator → HasOutputAnnotatorType
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final
val
outputCol: Param[String]
- Attributes
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- HasOutputAnnotationCol
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lazy val
params: Array[Param[_]]
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var
parent: Estimator[NerQuestionGenerator]
- Definition Classes
- Model
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val
questionMark: BooleanParam
Whether to add a question mark at the end of the question.
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val
questionPronoun: Param[String]
Pronoun to be used in the question.
Pronoun to be used in the question. E.g., 'When', 'Where', 'Why', 'How', 'Who', 'What'.
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def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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def
set[T](feature: StructFeature[T], value: T): NerQuestionGenerator.this.type
- Attributes
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- HasFeatures
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def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): NerQuestionGenerator.this.type
- Attributes
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- HasFeatures
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def
set[T](feature: SetFeature[T], value: Set[T]): NerQuestionGenerator.this.type
- Attributes
- protected
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- HasFeatures
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def
set[T](feature: ArrayFeature[T], value: Array[T]): NerQuestionGenerator.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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final
def
set(paramPair: ParamPair[_]): NerQuestionGenerator.this.type
- Attributes
- protected
- Definition Classes
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final
def
set(param: String, value: Any): NerQuestionGenerator.this.type
- Attributes
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- Definition Classes
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final
def
set[T](param: Param[T], value: T): NerQuestionGenerator.this.type
- Definition Classes
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def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): NerQuestionGenerator.this.type
- Attributes
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- Definition Classes
- HasFeatures
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def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): NerQuestionGenerator.this.type
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- HasFeatures
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def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): NerQuestionGenerator.this.type
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- HasFeatures
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def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): NerQuestionGenerator.this.type
- Attributes
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- HasFeatures
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final
def
setDefault(paramPairs: ParamPair[_]*): NerQuestionGenerator.this.type
- Attributes
- protected
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- Params
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final
def
setDefault[T](param: Param[T], value: T): NerQuestionGenerator.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
- def setEntities1(list: String*): NerQuestionGenerator.this.type
- def setEntities2(list: String*): NerQuestionGenerator.this.type
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final
def
setInputCols(value: String*): NerQuestionGenerator.this.type
- Definition Classes
- HasInputAnnotationCols
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def
setInputCols(value: Array[String]): NerQuestionGenerator.this.type
- Definition Classes
- HasInputAnnotationCols
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def
setLazyAnnotator(value: Boolean): NerQuestionGenerator.this.type
- Definition Classes
- CanBeLazy
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final
def
setOutputCol(value: String): NerQuestionGenerator.this.type
- Definition Classes
- HasOutputAnnotationCol
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def
setParent(parent: Estimator[NerQuestionGenerator]): NerQuestionGenerator
- Definition Classes
- Model
- def setQuestionMark(value: Boolean): NerQuestionGenerator
- def setQuestionPronoun(value: String): NerQuestionGenerator
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def
setStrategy(value: String): NerQuestionGenerator
Sets the strategy to be used in the proccess.
Sets the strategy to be used in the proccess. Either
Paired
orCombined
.If set to
Paired
(default), applies a one-vs-one strategy. In this case, the number of chunks in Entity 1 must be aligned with the number of chunks in Entity 2. E.g., if Entity 1 has 3 chunks and Entity 2 has 3 chunks, the first chunk of Entity 1 will be grouped with first chunk of Entity 2, the second with second, third with third, etc.If set to
Combined
, applies a one-vs-all strategy. In this case, the number of chunks in Entity 1 don't need to be the same as the number of chunks in Entity 2, and each chunk in Entity 1 will be grouped with all chunks in Entity 2. -
val
strategyType: Param[String]
Strategy for the proccess.
Strategy for the proccess. Either
Paired
orCombined
. -
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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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()
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final
def
transformSchema(schema: StructType): StructType
- Definition Classes
- RawAnnotator → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
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- @DeveloperApi()
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val
uid: String
- Definition Classes
- NerQuestionGenerator → Identifiable
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def
validate(schema: StructType): Boolean
- Attributes
- protected
- Definition Classes
- RawAnnotator
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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def
wait(arg0: Long): Unit
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def
wrapColumnMetadata(col: Column): Column
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
def
write: MLWriter
- Definition Classes
- ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
Inherited from CheckLicense
Inherited from HasSimpleAnnotate[NerQuestionGenerator]
Inherited from AnnotatorModel[NerQuestionGenerator]
Inherited from CanBeLazy
Inherited from RawAnnotator[NerQuestionGenerator]
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from HasOutputAnnotatorType
Inherited from ParamsAndFeaturesWritable
Inherited from HasFeatures
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Model[NerQuestionGenerator]
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