com.johnsnowlabs.nlp.annotators.re
RelationExtractionDLModel
Companion object RelationExtractionDLModel
class RelationExtractionDLModel extends AnnotatorModel[RelationExtractionDLModel] with WriteTensorflowModel with HasStorageRef with HasCaseSensitiveProperties with HasSimpleAnnotate[RelationExtractionDLModel] with RelationEncoding with HasEngine with HandleExceptionParams with HasSafeAnnotate[RelationExtractionDLModel] with CheckLicense
Extracts and classifies instances of relations between named entities. In contrast with RelationExtractionModel, RelationExtractionDLModel is based on BERT. For pretrained models please see the Models Hub for available models.
Example
Relation Extraction between body parts
This is a continuation of the RENerChunksFilter example. See that class on how to extract the relation chunks. Define the extraction model
val re_ner_chunk_filter = new RENerChunksFilter() .setInputCols("ner_chunks", "dependencies") .setOutputCol("re_ner_chunks") .setMaxSyntacticDistance(4) .setRelationPairs(Array("internal_organ_or_component-direction")) val re_model = RelationExtractionDLModel.pretrained("redl_bodypart_direction_biobert", "en", "clinical/models") .setPredictionThreshold(0.5f) .setInputCols("re_ner_chunks", "sentences") .setOutputCol("relations") val trained_pipeline = new Pipeline().setStages(Array( documenter, sentencer, tokenizer, words_embedder, pos_tagger, clinical_ner_tagger, ner_chunker, dependency_parser, re_ner_chunk_filter, re_model )) val data = Seq("MRI demonstrated infarction in the upper brain stem , left cerebellum and right basil ganglia").toDF("text") val result = trained_pipeline.fit(data).transform(data)
Show results
result.selectExpr("explode(relations) as relations") .select( "relations.metadata.chunk1", "relations.metadata.entity1", "relations.metadata.chunk2", "relations.metadata.entity2", "relations.result" ) .where("result != 0") .show(truncate=false) +------+---------+-------------+---------------------------+------+ |chunk1|entity1 |chunk2 |entity2 |result| +------+---------+-------------+---------------------------+------+ |upper |Direction|brain stem |Internal_organ_or_component|1 | |left |Direction|cerebellum |Internal_organ_or_component|1 | |right |Direction|basil ganglia|Internal_organ_or_component|1 | +------+---------+-------------+---------------------------+------+
- See also
RelationExtractionModel for ML based extraction
RENerChunksFilter on how to create inputs
- Grouped
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- By Inheritance
- RelationExtractionDLModel
- CheckLicense
- HasSafeAnnotate
- HandleExceptionParams
- HasEngine
- RelationEncoding
- HasSimpleAnnotate
- HasCaseSensitiveProperties
- HasStorageRef
- WriteTensorflowModel
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
- HasFeatures
- DefaultParamsWritable
- MLWritable
- Model
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
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final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
$[T](param: Param[T]): T
- Attributes
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- 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
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- Definition Classes
- HasFeatures
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final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
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]
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
- RelationExtractionDLModel → HasSimpleAnnotate
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
var
batchSize: IntParam
Size of the batches to process.
-
def
beforeAnnotate(dataset: Dataset[_]): Dataset[_]
- Definition Classes
- RelationExtractionDLModel → AnnotatorModel
- var bertREConfig: BertREConfig
-
val
caseSensitive: BooleanParam
- Definition Classes
- HasCaseSensitiveProperties
-
def
categorizeRelations(relations: Seq[DLRelationInstance]): Seq[(Int, Int, Float)]
- Attributes
- protected
-
var
categoryNames: StringArrayParam
List of relation names.
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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
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val
classes: StringArrayParam
Categorization classes
-
final
def
clear(param: Param[_]): RelationExtractionDLModel.this.type
- Definition Classes
- Params
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
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val
configProtoBytes: IntArrayParam
ConfigProto from tensorflow, serialized into byte array.
ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()
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def
copy(extra: ParamMap): RelationExtractionDLModel
- Definition Classes
- RawAnnotator → Model → Transformer → PipelineStage → Params
-
def
copyValues[T <: Params](to: T, extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
def
createDatabaseConnection(database: Name): RocksDBConnection
- Definition Classes
- HasStorageRef
-
var
customLabels: MapFeature[String, String]
Custom relation labels
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final
def
defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
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def
dfAnnotate: UserDefinedFunction
- Definition Classes
- HasSimpleAnnotate
-
val
doExceptionHandling: BooleanParam
If true, exceptions are handled.
If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.
- Definition Classes
- HandleExceptionParams
-
def
encodeRelations(nerChunkAnnotations: Seq[Annotation], sentenceAnnotations: Seq[Annotation]): Seq[DLRelationInstance]
- Definition Classes
- RelationEncoding
-
val
engine: Param[String]
- Definition Classes
- HasEngine
-
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
-
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
get[T](feature: StructFeature[T]): Option[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
get[T](feature: SetFeature[T]): Option[Set[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
get[T](feature: ArrayFeature[T]): Option[Array[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
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final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getBatchSize: Int
Number of relations to process in a batch
-
def
getCaseSensitive: Boolean
- Definition Classes
- HasCaseSensitiveProperties
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def
getCategories(): Array[String]
Get all categories
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def
getCategoryName(id: Int): String
List of relation names
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final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
getClasses: Array[String]
Proxy to getCategories
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def
getConfigProtoBytes: Option[Array[Byte]]
ConfigProto from tensorflow, serialized into byte array.
ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()
-
def
getCustomLabel(label: String): String
Gets the custom relation label for a given label.
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def
getCustomLabels: Map[String, String]
Gets all custom relation labels.
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final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getEngine: String
- Definition Classes
- HasEngine
-
def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
def
getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
-
def
getMaxSentenceLength: Int
Max sentence length to process (Default : 128)
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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
getPredictionThreshold: Float
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
-
def
getRelationPairsCaseSensitive: Boolean
Gets the case sensitivity of relation pairs
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def
getRelationTypePerPair: Map[String, Array[String]]
Get the lists of entity pairs allowed for a given relation
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def
getRelationTypePerPairStr: String
Get a string representation of the lists of entity pairs allowed for a given relation
-
def
getStorageRef: String
- Definition Classes
- HasStorageRef
-
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()
-
val
inExceptionMode: Boolean
- Attributes
- protected
- Definition Classes
- HasSafeAnnotate
-
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[AnnotatorType]
Input annotator types : CHUNK, DOCUMENT
Input annotator types : CHUNK, DOCUMENT
- Definition Classes
- RelationExtractionDLModel → HasInputAnnotationCols
-
final
val
inputCols: StringArrayParam
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
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final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
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final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
def
isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
val
lazyAnnotator: BooleanParam
- Definition Classes
- CanBeLazy
-
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
-
val
maxSentenceLength: IntParam
Max sentence length to process (Default : 128)
- def model: TensorflowBertRE
-
def
msgHelper(schema: StructType): String
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
def
onWrite(path: String, spark: SparkSession): Unit
- Definition Classes
- RelationExtractionDLModel → ParamsAndFeaturesWritable
-
val
optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
val
outputAnnotatorType: String
Output annotator type : CATEGORY
Output annotator type : CATEGORY
- Definition Classes
- RelationExtractionDLModel → HasOutputAnnotatorType
-
final
val
outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
var
parent: Estimator[RelationExtractionDLModel]
- Definition Classes
- Model
-
var
predictionThreshold: FloatParam
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
-
var
relationPairsCaseSensitive: BooleanParam
Determines whether relation pairs are case sensitive
-
def
safeAnnotate(annotations: Seq[Annotation]): Seq[Annotation]
A protected method designed to safely annotate a sequence of Annotation objects by handling exceptions.
A protected method designed to safely annotate a sequence of Annotation objects by handling exceptions.
- annotations
A sequence of Annotation.
- returns
A sequence of Annotation objects after processing, potentially containing error annotations.
- Attributes
- protected
- Definition Classes
- HasSafeAnnotate
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
-
def
set[T](feature: StructFeature[T], value: T): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: SetFeature[T], value: Set[T]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: ArrayFeature[T], value: Array[T]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
set(paramPair: ParamPair[_]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): RelationExtractionDLModel.this.type
- Definition Classes
- Params
-
def
setBatchSize(size: Int): RelationExtractionDLModel.this.type
Set the number of relations to process in a batch.
Set the number of relations to process in a batch. Using a larger value speeds up processing but requires more memory.
-
def
setCaseSensitive(value: Boolean): RelationExtractionDLModel.this.type
- Definition Classes
- HasCaseSensitiveProperties
-
def
setCategoryNames(categoryNames: Array[String]): RelationExtractionDLModel.this.type
List of relation names
-
def
setConfigProtoBytes(bytes: Array[Int]): RelationExtractionDLModel.this.type
ConfigProto from tensorflow, serialized into byte array.
ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()
- def setCustomLabels(labels: HashMap[String, String]): RelationExtractionDLModel.this.type
-
def
setCustomLabels(labels: Map[String, String]): RelationExtractionDLModel.this.type
Set custom relation labels
-
def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
setDefault(paramPairs: ParamPair[_]*): RelationExtractionDLModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): RelationExtractionDLModel.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
-
def
setDoExceptionHandling(value: Boolean): RelationExtractionDLModel.this.type
If true, exceptions are handled.
If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.
- Definition Classes
- HandleExceptionParams
-
final
def
setInputCols(value: String*): RelationExtractionDLModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setInputCols(value: Array[String]): RelationExtractionDLModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setLazyAnnotator(value: Boolean): RelationExtractionDLModel.this.type
- Definition Classes
- CanBeLazy
-
def
setMaxSentenceLength(value: Int): RelationExtractionDLModel.this.type
Max sentence length to process (Default : 128)
-
final
def
setOutputCol(value: String): RelationExtractionDLModel.this.type
- Definition Classes
- HasOutputAnnotationCol
-
def
setParent(parent: Estimator[RelationExtractionDLModel]): RelationExtractionDLModel
- Definition Classes
- Model
-
def
setPredictionThreshold(predictionThreshold: Float): RelationExtractionDLModel.this.type
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
-
def
setRelationPairsCaseSensitive(value: Boolean): RelationExtractionDLModel.this.type
Sets the case sensitivity of relation pairs
-
def
setRelationTypePerPair(categories: HashMap[String, List[String]]): RelationExtractionDLModel.this.type
Set the lists of entity pairs allowed for a given relation
-
def
setRelationTypePerPair(categories: Map[String, Array[String]]): RelationExtractionDLModel.this.type
Set the lists of entity pairs allowed for a given relation
-
def
setStorageRef(value: String): RelationExtractionDLModel.this.type
- Definition Classes
- HasStorageRef
- def setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): RelationExtractionDLModel.this.type
-
def
setVocabulary(value: Map[String, Int]): RelationExtractionDLModel.this.type
Vocabulary used to encode words to ids with WordPieceEncoder
-
val
storageRef: Param[String]
- Definition Classes
- HasStorageRef
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
- def tokenizeSentence(sentence: Sentence): WordpieceTokenizedSentence
-
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
- RelationExtractionDLModel → Identifiable
- def updateBertConfig: Unit
-
def
validate(schema: StructType): Boolean
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
def
validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
- Definition Classes
- HasStorageRef
-
val
vocabulary: MapFeature[String, Int]
Vocabulary used to encode words to ids with WordPieceEncoder
-
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
-
def
writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
- Definition Classes
- WriteTensorflowModel
-
def
writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
- Definition Classes
- WriteTensorflowModel
-
def
writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
- Definition Classes
- WriteTensorflowModel
Inherited from CheckLicense
Inherited from HasSafeAnnotate[RelationExtractionDLModel]
Inherited from HandleExceptionParams
Inherited from HasEngine
Inherited from RelationEncoding
Inherited from HasSimpleAnnotate[RelationExtractionDLModel]
Inherited from HasCaseSensitiveProperties
Inherited from HasStorageRef
Inherited from WriteTensorflowModel
Inherited from AnnotatorModel[RelationExtractionDLModel]
Inherited from CanBeLazy
Inherited from RawAnnotator[RelationExtractionDLModel]
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from HasOutputAnnotatorType
Inherited from ParamsAndFeaturesWritable
Inherited from HasFeatures
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Model[RelationExtractionDLModel]
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
Annotator types
Required input and expected output annotator types