Packages

class TypedDependencyParserApproach extends AnnotatorApproach[TypedDependencyParserModel]

Labeled parser that finds a grammatical relation between two words in a sentence. Its input is either a CoNLL2009 or ConllU dataset.

For instantiated/pretrained models, see TypedDependencyParserModel.

Dependency parsers provide information about word relationship. For example, dependency parsing can tell you what the subjects and objects of a verb are, as well as which words are modifying (describing) the subject. This can help you find precise answers to specific questions.

The parser requires the dependant tokens beforehand with e.g. DependencyParser. The required training data can be set in two different ways (only one can be chosen for a particular model):

Apart from that, no additional training data is needed.

See TypedDependencyParserApproachTestSpec for further reference on this API.

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.pos.perceptron.PerceptronModel
import com.johnsnowlabs.nlp.annotators.parser.dep.DependencyParserModel
import com.johnsnowlabs.nlp.annotators.parser.typdep.TypedDependencyParserApproach
import org.apache.spark.ml.Pipeline

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

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

val typedDependencyParser = new TypedDependencyParserApproach()
  .setInputCols("dependency", "pos", "token")
  .setOutputCol("dependency_type")
  .setConllU("src/test/resources/parser/labeled/train_small.conllu.txt")
  .setNumberOfIterations(1)

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

// Additional training data is not needed, the dependency parser relies on CoNLL-U only.
val emptyDataSet = Seq.empty[String].toDF("text")
val pipelineModel = pipeline.fit(emptyDataSet)
Linear Supertypes
AnnotatorApproach[TypedDependencyParserModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[TypedDependencyParserModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TypedDependencyParserApproach
  2. AnnotatorApproach
  3. CanBeLazy
  4. DefaultParamsWritable
  5. MLWritable
  6. HasOutputAnnotatorType
  7. HasOutputAnnotationCol
  8. HasInputAnnotationCols
  9. Estimator
  10. PipelineStage
  11. Logging
  12. Params
  13. Serializable
  14. Serializable
  15. Identifiable
  16. AnyRef
  17. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

Type Members

  1. 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. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): TypedDependencyParserModel
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. def beforeTraining(spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  8. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  9. final def clear(param: Param[_]): TypedDependencyParserApproach.this.type
    Definition Classes
    Params
  10. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  11. val conll2009: ExternalResourceParam

    Path to file with CoNLL 2009 format

  12. val conllU: ExternalResourceParam

    Universal Dependencies source files

  13. final def copy(extra: ParamMap): Estimator[TypedDependencyParserModel]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  14. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  16. val description: String

    Typed Dependency Parser is a labeled parser that finds a grammatical relation between two words in a sentence

    Typed Dependency Parser is a labeled parser that finds a grammatical relation between two words in a sentence

    Definition Classes
    TypedDependencyParserApproachAnnotatorApproach
  17. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  19. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  20. def explainParams(): String
    Definition Classes
    Params
  21. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  22. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  23. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  24. final def fit(dataset: Dataset[_]): TypedDependencyParserModel
    Definition Classes
    AnnotatorApproach → Estimator
  25. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TypedDependencyParserModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  26. def fit(dataset: Dataset[_], paramMap: ParamMap): TypedDependencyParserModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TypedDependencyParserModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  28. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  29. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  30. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  31. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  32. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  33. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  34. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  35. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  36. def getTrainingFile: TrainFile
  37. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  38. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  39. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  40. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  41. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  42. val inputAnnotatorTypes: Array[String]

    Input annotation type : TOKEN, POS, DEPENDENCY

    Input annotation type : TOKEN, POS, DEPENDENCY

    Definition Classes
    TypedDependencyParserApproachHasInputAnnotationCols
  43. 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
  44. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  45. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  46. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  47. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  48. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  49. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  50. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  57. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  62. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  63. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  64. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  65. val numberOfIterations: IntParam

    Number of iterations in training, converges to better accuracy (Default: 10)

  66. def onTrained(model: TypedDependencyParserModel, spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  67. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  68. val outputAnnotatorType: String

    Input annotation type : LABELED_DEPENDENCY

    Input annotation type : LABELED_DEPENDENCY

    Definition Classes
    TypedDependencyParserApproachHasOutputAnnotatorType
  69. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  70. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  71. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  72. final def set(paramPair: ParamPair[_]): TypedDependencyParserApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  73. final def set(param: String, value: Any): TypedDependencyParserApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  74. final def set[T](param: Param[T], value: T): TypedDependencyParserApproach.this.type
    Definition Classes
    Params
  75. def setConll2009(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map.empty[String, String]): TypedDependencyParserApproach.this.type

    Path to a file in CoNLL 2009 format

  76. def setConllU(path: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map.empty[String, String]): TypedDependencyParserApproach.this.type

    Path to a file in CoNLL-U format

  77. final def setDefault(paramPairs: ParamPair[_]*): TypedDependencyParserApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  78. final def setDefault[T](param: Param[T], value: T): TypedDependencyParserApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  79. final def setInputCols(value: String*): TypedDependencyParserApproach.this.type
    Definition Classes
    HasInputAnnotationCols
  80. final def setInputCols(value: Array[String]): TypedDependencyParserApproach.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  81. def setLazyAnnotator(value: Boolean): TypedDependencyParserApproach.this.type
    Definition Classes
    CanBeLazy
  82. def setNumberOfIterations(value: Int): TypedDependencyParserApproach.this.type

    Number of iterations in training, converges to better accuracy

  83. final def setOutputCol(value: String): TypedDependencyParserApproach.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  84. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  85. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  86. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): TypedDependencyParserModel
  87. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    AnnotatorApproach → PipelineStage
  88. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  89. val uid: String
    Definition Classes
    TypedDependencyParserApproach → Identifiable
  90. 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
    AnnotatorApproach
  91. def validateTrainingFiles(): Unit
  92. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  93. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  94. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  95. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[TypedDependencyParserModel]

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