RelationExtractionModel

Instance Constructors

new RelationExtractionModel()
new RelationExtractionModel(uid: String)

Type Members

type AnnotationContent = Seq[Row]

Attributes
protected
Definition Classes
AnnotatorModel
type AnnotatorType = String

Definition Classes
HasOutputAnnotatorType

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
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
RelationExtractionModel → GenericClassifierModel → AnnotatorModel
final def asInstanceOf[T0]: T0

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

Definition Classes
RelationExtractionModel → GenericClassifierModel → AnnotatorModel
def categorizeRel(relation: RelationInstance): (Long, Float)

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

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def clear(param: Param[_]): RelationExtractionModel.this.type

Definition Classes
Params
def clone(): AnyRef

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

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
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
def dfAnnotate: UserDefinedFunction

Attributes
protected
Definition Classes
AnnotatorModel
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 featureScaling: Param[String]

Feature scaling method.
Feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)

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

Definition Classes
HasFeatures
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
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 getCategories(): Array[String]

Get all categories
Get all categories

Definition Classes
GenericClassifierModel
def getCategoryName(id: Int): String

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

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

Definition Classes
Params
def getEncoder: GenericClassifierDataEncoder

Definition Classes
GenericClassifierModel
def getFeatureScaling: String

Get feature scaling method
Get feature scaling method

Definition Classes
GenericClassifierModel
def getInputCols: Array[String]

Definition Classes
HasInputAnnotationCols
def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
def getMaxSyntacticDistance: Float

Get prediction threshold
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

Get prediction threshold
def getRelationPairs: Array[String]

Get relation pairs
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
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]

Output annotator type : SENTENCE_EMBEDDINGS
Output annotator type : SENTENCE_EMBEDDINGS

Definition Classes
RelationExtractionModel → GenericClassifierModel → 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
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
def loadModel(sparkSession: SparkSession, tfModel: TensorflowWrapper, categories: Array[String], encoder: GenericClassifierDataEncoder, nerTags: Array[String]): RelationExtractionModel.this.type
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
var maxSyntacticDistance: IntParam
def model: TensorflowGenericClassifier

Definition Classes
GenericClassifierModel
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
final def notifyAll(): Unit

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

Definition Classes
GenericClassifierModel → ParamsAndFeaturesWritable
val outputAnnotatorType: String

Output annotator type : CATEGORY
Output annotator type : CATEGORY

Definition Classes
RelationExtractionModel → GenericClassifierModel → HasOutputAnnotatorType
final val outputCol: Param[String]

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

Definition Classes
Params
var parent: Estimator[GenericClassifierModel]

Definition Classes
Model
var predictionThreshold: FloatParam
var relationPairs: Param[String]

List of pairs of named entities ("ENTITY1-ENTITY2", e.g.
List of pairs of named entities ("ENTITY1-ENTITY2", e.g. "Biomarker-RelativeDay"), which will be processed
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
def scaleFeatures(features: Array[Array[Float]]): Array[Array[Float]]

Attributes
protected
Definition Classes
GenericClassifierModel
def set[T](feature: StructFeature[T], value: T): RelationExtractionModel.this.type

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

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

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

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

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

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

Definition Classes
Params
def setCategoryNames(categoryNames: Array[String]): RelationExtractionModel.this.type

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

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

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

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

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

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

Attributes
protected
Definition Classes
Params
def setEncoder(encoder: GenericClassifierDataEncoder): RelationExtractionModel.this.type

Definition Classes
GenericClassifierModel
def setFeatureScaling(featureScaling: String): RelationExtractionModel.this.type

Set the feature scaling method.
Set the feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)

Definition Classes
GenericClassifierModel
final def setInputCols(value: String*): RelationExtractionModel.this.type

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

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

Definition Classes
CanBeLazy
def setMaxSyntacticDistance(maxSyntacticDistance: Int): RelationExtractionModel.this.type

Set prediction threshold
final def setOutputCol(value: String): RelationExtractionModel.this.type

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

Definition Classes
Model
def setPredictionThreshold(predictionThreshold: Float): RelationExtractionModel.this.type

Set prediction threshold
def setRelationPairs(relationPairs: Array[String]): RelationExtractionModel.this.type

Set relation pairs
def setStorageRef(value: String): RelationExtractionModel.this.type

Definition Classes
HasStorageRef
def setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): RelationExtractionModel.this.type

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

Attributes
protected
Definition Classes
RawAnnotator
def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit

Definition Classes
HasStorageRef
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( ... )
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]]): Unit

Definition Classes
WriteTensorflowModel

Related Docs: object RelationExtractionModel | package re

class RelationExtractionModel extends GenericClassifierModel

Instance Constructors

new RelationExtractionModel()

new RelationExtractionModel(uid: String)

Type Members

type AnnotationContent = Seq[Row]

type AnnotatorType = String

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

def $$[T](feature: StructFeature[T]): T

def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

def $$[T](feature: SetFeature[T]): Set[T]

def $$[T](feature: ArrayFeature[T]): Array[T]

final def ==(arg0: Any): Boolean

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

def afterAnnotate(dataset: DataFrame): DataFrame

def annotate(annotations: Seq[Annotation]): Seq[Annotation]

final def asInstanceOf[T0]: T0

def beforeAnnotate(dataset: Dataset[_]): Dataset[_]

def categorizeRel(relation: RelationInstance): (Long, Float)

final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

final def clear(param: Param[_]): RelationExtractionModel.this.type

def clone(): AnyRef

def copy(extra: ParamMap): GenericClassifierModel

def copyValues[T <: Params](to: T, extra: ParamMap): T

def createDatabaseConnection(database: Name): RocksDBConnection

final def defaultCopy[T <: Params](extra: ParamMap): T

def dfAnnotate: UserDefinedFunction

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

def extraValidate(structType: StructType): Boolean

def extraValidateMsg: String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

val featureScaling: Param[String]

val features: ArrayBuffer[Feature[_, _, _]]

def finalize(): Unit

def get[T](feature: StructFeature[T]): Option[T]

def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

def get[T](feature: SetFeature[T]): Option[Set[T]]

def get[T](feature: ArrayFeature[T]): Option[Array[T]]

final def get[T](param: Param[T]): Option[T]

def getCategories(): Array[String]

def getCategoryName(id: Int): String

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

def getEncoder: GenericClassifierDataEncoder

def getFeatureScaling: String

def getInputCols: Array[String]

def getLazyAnnotator: Boolean

def getMaxSyntacticDistance: Float

final def getOrDefault[T](param: Param[T]): T

final def getOutputCol: String

def getParam(paramName: String): Param[Any]

def getPredictionThreshold: Float

def getRelationPairs: Array[String]

def getStorageRef: String

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

def hasParam(paramName: String): Boolean

def hasParent: Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

val inputAnnotatorTypes: Array[AnnotatorType]

final val inputCols: StringArrayParam

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

val lazyAnnotator: BooleanParam

def loadModel(sparkSession: SparkSession, tfModel: TensorflowWrapper, categories: Array[String], encoder: GenericClassifierDataEncoder, nerTags: Array[String]): RelationExtractionModel.this.type

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit