Packages

c

com.johnsnowlabs.nlp.annotators

GraphExtraction

class GraphExtraction extends AnnotatorModel[GraphExtraction] with HasSimpleAnnotate[GraphExtraction]

Extracts a dependency graph between entities.

The GraphExtraction class takes e.g. extracted entities from a NerDLModel and creates a dependency tree which describes how the entities relate to each other. For that a triple store format is used. Nodes represent the entities and the edges represent the relations between those entities. The graph can then be used to find relevant relationships between words.

Both the DependencyParserModel and TypedDependencyParserModel need to be present in the pipeline. There are two ways to set them:

  1. Both Annotators are present in the pipeline already. The dependencies are taken implicitly from these two Annotators.
  2. Setting setMergeEntities to true will download the default pretrained models for those two Annotators automatically. The specific models can also be set with setDependencyParserModel and setTypedDependencyParserModel:
val graph_extraction = new GraphExtraction()
  .setInputCols("document", "token", "ner")
  .setOutputCol("graph")
  .setRelationshipTypes(Array("prefer-LOC"))
  .setMergeEntities(true)
//.setDependencyParserModel(Array("dependency_conllu", "en",  "public/models"))
//.setTypedDependencyParserModel(Array("dependency_typed_conllu", "en",  "public/models"))

To transform the resulting graph into a more generic form such as RDF, see the GraphFinisher.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.sbd.pragmatic.SentenceDetector
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.annotators.ner.dl.NerDLModel
import com.johnsnowlabs.nlp.embeddings.WordEmbeddingsModel
import com.johnsnowlabs.nlp.annotators.pos.perceptron.PerceptronModel
import com.johnsnowlabs.nlp.annotators.parser.dep.DependencyParserModel
import com.johnsnowlabs.nlp.annotators.parser.typdep.TypedDependencyParserModel
import org.apache.spark.ml.Pipeline
import com.johnsnowlabs.nlp.annotators.GraphExtraction

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

val sentence = new SentenceDetector()
  .setInputCols("document")
  .setOutputCol("sentence")

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

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

val nerTagger = NerDLModel.pretrained()
  .setInputCols("sentence", "token", "embeddings")
  .setOutputCol("ner")

val posTagger = PerceptronModel.pretrained()
  .setInputCols("sentence", "token")
  .setOutputCol("pos")

val dependencyParser = DependencyParserModel.pretrained()
  .setInputCols("sentence", "pos", "token")
  .setOutputCol("dependency")

val typedDependencyParser = TypedDependencyParserModel.pretrained()
  .setInputCols("dependency", "pos", "token")
  .setOutputCol("dependency_type")

val graph_extraction = new GraphExtraction()
  .setInputCols("document", "token", "ner")
  .setOutputCol("graph")
  .setRelationshipTypes(Array("prefer-LOC"))

val pipeline = new Pipeline().setStages(Array(
  documentAssembler,
  sentence,
  tokenizer,
  embeddings,
  nerTagger,
  posTagger,
  dependencyParser,
  typedDependencyParser,
  graph_extraction
))

val data = Seq("You and John prefer the morning flight through Denver").toDF("text")
val result = pipeline.fit(data).transform(data)

result.select("graph").show(false)
+-----------------------------------------------------------------------------------------------------------------+
|graph                                                                                                            |
+-----------------------------------------------------------------------------------------------------------------+
|[[node, 13, 18, prefer, [relationship -> prefer,LOC, path1 -> prefer,nsubj,morning,flat,flight,flat,Denver], []]]|
+-----------------------------------------------------------------------------------------------------------------+
See also

GraphFinisher to output the paths in a more generic format, like RDF

Linear Supertypes
HasSimpleAnnotate[GraphExtraction], AnnotatorModel[GraphExtraction], CanBeLazy, RawAnnotator[GraphExtraction], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[GraphExtraction], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. GraphExtraction
  2. HasSimpleAnnotate
  3. AnnotatorModel
  4. CanBeLazy
  5. RawAnnotator
  6. HasOutputAnnotationCol
  7. HasInputAnnotationCols
  8. HasOutputAnnotatorType
  9. ParamsAndFeaturesWritable
  10. HasFeatures
  11. DefaultParamsWritable
  12. MLWritable
  13. Model
  14. Transformer
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new GraphExtraction()
  2. new GraphExtraction(uid: String)

    uid

    required uid for storing annotator to disk

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
    Definition Classes
    GraphExtraction → AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  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
    GraphExtraction → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Definition Classes
    GraphExtraction → AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. final def clear(param: Param[_]): GraphExtraction.this.type
    Definition Classes
    Params
  16. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  17. def copy(extra: ParamMap): GraphExtraction

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  18. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  19. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. val delimiter: Param[String]

    Delimiter symbol used for path output (Default: ",")

  21. val dependencyParserModel: StringArrayParam

    Coordinates (name, lang, remoteLoc) to a pretrained Dependency Parser model (Default: Array())

  22. 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
  23. val entityTypes: StringArrayParam

    Find paths between a pair of entities (Default: Array())

  24. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  25. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  26. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  27. def explainParams(): String
    Definition Classes
    Params
  28. val explodeEntities: BooleanParam

    When set to true find paths between entities (Default: false)

  29. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  30. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

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

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  43. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  44. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  45. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  46. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  47. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  48. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  49. def hasParent: Boolean
    Definition Classes
    Model
  50. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  51. val includeEdges: BooleanParam

    Whether to include edges when building paths (Default: true)

  52. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  53. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. val inputAnnotatorTypes: Array[String]

    Input annotator types: DOCUMENT, TOKEN, NAMED_ENTITY

    Input annotator types: DOCUMENT, TOKEN, NAMED_ENTITY

    Definition Classes
    GraphExtraction → HasInputAnnotationCols
  55. 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
  56. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  57. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  58. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  59. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  60. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  61. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  62. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. val maxSentenceSize: IntParam

    Maximum sentence size that the annotator will process (Default: 1000).

    Maximum sentence size that the annotator will process (Default: 1000). Above this, the sentence is skipped

  74. val mergeEntities: BooleanParam

    Merge same neighboring entities as a single token (Default: false)

  75. val mergeEntitiesIOBFormat: Param[String]

    IOB format to apply when merging entities

  76. val minSentenceSize: IntParam

    Minimum sentence size that the annotator will process (Default: 2).

    Minimum sentence size that the annotator will process (Default: 2). Below this, the sentence is skipped

  77. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  78. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  79. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  80. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  81. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  82. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    GraphExtraction → HasInputAnnotationCols
  83. val outputAnnotatorType: AnnotatorType

    Output annotator types: NODE

    Output annotator types: NODE

    Definition Classes
    GraphExtraction → HasOutputAnnotatorType
  84. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  85. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  86. var parent: Estimator[GraphExtraction]
    Definition Classes
    Model
  87. val posModel: StringArrayParam

    Coordinates (name, lang, remoteLoc) to a pretrained POS model (Default: Array())

  88. val relationshipTypes: StringArrayParam

    Find paths between a pair of token and entity (Default: Array())

  89. val rootTokens: StringArrayParam

    Tokens to be consider as root to start traversing the paths (Default: Array()).

    Tokens to be consider as root to start traversing the paths (Default: Array()). Use it along with explodeEntities

  90. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  91. def set[T](feature: StructFeature[T], value: T): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  92. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  93. def set[T](feature: SetFeature[T], value: Set[T]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  94. def set[T](feature: ArrayFeature[T], value: Array[T]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  95. final def set(paramPair: ParamPair[_]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    Params
  96. final def set(param: String, value: Any): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    Params
  97. final def set[T](param: Param[T], value: T): GraphExtraction.this.type
    Definition Classes
    Params
  98. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. final def setDefault(paramPairs: ParamPair[_]*): GraphExtraction.this.type
    Attributes
    protected
    Definition Classes
    Params
  103. final def setDefault[T](param: Param[T], value: T): GraphExtraction.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  104. def setDelimiter(value: String): GraphExtraction.this.type

  105. def setDependencyParserModel(value: Array[String]): GraphExtraction.this.type

  106. def setEntityTypes(value: Array[String]): GraphExtraction.this.type

  107. def setExplodeEntities(value: Boolean): GraphExtraction.this.type

  108. def setIncludeEdges(value: Boolean): GraphExtraction.this.type

  109. final def setInputCols(value: String*): GraphExtraction.this.type
    Definition Classes
    HasInputAnnotationCols
  110. def setInputCols(value: Array[String]): GraphExtraction.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  111. def setLazyAnnotator(value: Boolean): GraphExtraction.this.type
    Definition Classes
    CanBeLazy
  112. def setMaxSentenceSize(value: Int): GraphExtraction.this.type

  113. def setMergeEntities(value: Boolean): GraphExtraction.this.type

  114. def setMergeEntitiesIOBFormat(value: String): GraphExtraction.this.type

  115. def setMinSentenceSize(value: Int): GraphExtraction.this.type

  116. final def setOutputCol(value: String): GraphExtraction.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  117. def setParent(parent: Estimator[GraphExtraction]): GraphExtraction
    Definition Classes
    Model
  118. def setPosModel(value: Array[String]): GraphExtraction.this.type

  119. def setRelationshipTypes(value: Array[String]): GraphExtraction.this.type

  120. def setRootTokens(value: Array[String]): GraphExtraction.this.type

  121. def setTypedDependencyParserModel(value: Array[String]): GraphExtraction.this.type

  122. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  123. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  124. 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
  125. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  126. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  127. 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
  128. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  129. val typedDependencyParserModel: StringArrayParam

    Coordinates (name, lang, remoteLoc) to a pretrained Typed Dependency Parser model (Default: Array())

  130. val uid: String
    Definition Classes
    GraphExtraction → Identifiable
  131. 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
  132. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  133. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  134. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  135. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  136. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from HasSimpleAnnotate[GraphExtraction]

Inherited from AnnotatorModel[GraphExtraction]

Inherited from CanBeLazy

Inherited from RawAnnotator[GraphExtraction]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[GraphExtraction]

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