Packages

class Lemmatizer extends AnnotatorApproach[LemmatizerModel]

Class to find standarized lemmas from words. Uses a user-provided or default dictionary.

Retrieves lemmas out of words with the objective of returning a base dictionary word. Retrieves the significant part of a word.

lemmaDict: A dictionary of predefined lemmas must be provided

See https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/LemmatizerTestSpec.scala for examples of how to use this API

Linear Supertypes
AnnotatorApproach[LemmatizerModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[LemmatizerModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. Lemmatizer
  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 Lemmatizer()
  2. new Lemmatizer(uid: String)

    uid

    required internal uid provided by constructor

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]): LemmatizerModel
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  6. def arraysZip: UserDefinedFunction
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. def beforeTraining(spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  9. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  10. final def clear(param: Param[_]): Lemmatizer.this.type
    Definition Classes
    Params
  11. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  12. final def copy(extra: ParamMap): Estimator[LemmatizerModel]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  13. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. val description: String

    Retrieves the significant part of a word

    Retrieves the significant part of a word

    Definition Classes
    Lemmatizer → AnnotatorApproach
  16. val dictionary: ExternalResourceParam

    lemmatizer external dictionary, needs 'keyDelimiter' and 'valueDelimiter' in options for parsing target text

  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[_]): LemmatizerModel
    Definition Classes
    AnnotatorApproach → Estimator
  25. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[LemmatizerModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  26. def fit(dataset: Dataset[_], paramMap: ParamMap): LemmatizerModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): LemmatizerModel
    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 getDictionary: ExternalResource

    Path and options to lemma dictionary, in lemma vs possible words format.

    Path and options to lemma dictionary, in lemma vs possible words format. readAs can be LINE_BY_LINE or SPARK_DATASET. options contain option passed to spark reader if readAs is SPARK_DATASET. lemmatizer external dictionary

  32. def getInputCols: Array[String]

    returns

    input annotations columns currently used

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

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  36. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  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[AnnotatorType]

    Input annotator type : TOKEN

    Input annotator type : TOKEN

    Definition Classes
    Lemmatizer → HasInputAnnotationCols
  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. def onTrained(model: LemmatizerModel, spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  66. val outputAnnotatorType: AnnotatorType

    Output annotator type : TOKEN

    Output annotator type : TOKEN

    Definition Classes
    Lemmatizer → HasOutputAnnotatorType
  67. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  68. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  69. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  70. final def set(paramPair: ParamPair[_]): Lemmatizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  71. final def set(param: String, value: Any): Lemmatizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  72. final def set[T](param: Param[T], value: T): Lemmatizer.this.type
    Definition Classes
    Params
  73. final def setDefault(paramPairs: ParamPair[_]*): Lemmatizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  74. final def setDefault[T](param: Param[T], value: T): Lemmatizer.this.type
    Attributes
    protected
    Definition Classes
    Params
  75. def setDictionary(path: String, keyDelimiter: String, valueDelimiter: String, readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("format" -> "text")): Lemmatizer.this.type

    setDictionary(path, keyDelimiter, valueDelimiter, readAs, options): Path and options to lemma dictionary, in lemma vs possible words format.

    setDictionary(path, keyDelimiter, valueDelimiter, readAs, options): Path and options to lemma dictionary, in lemma vs possible words format. readAs can be LINE_BY_LINE or SPARK_DATASET. options contain option passed to spark reader if readAs is SPARK_DATASET. lemmatizer external dictionary

  76. def setDictionary(value: ExternalResource): Lemmatizer.this.type

    setDictionary(path, keyDelimiter, valueDelimiter, readAs, options): Path and options to lemma dictionary, in lemma vs possible words format.

    setDictionary(path, keyDelimiter, valueDelimiter, readAs, options): Path and options to lemma dictionary, in lemma vs possible words format. readAs can be LINE_BY_LINE or SPARK_DATASET. options contain option passed to spark reader if readAs is SPARK_DATASET. lemmatizer external dictionary

  77. final def setInputCols(value: String*): Lemmatizer.this.type
    Definition Classes
    HasInputAnnotationCols
  78. final def setInputCols(value: Array[String]): Lemmatizer.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  79. def setLazyAnnotator(value: Boolean): Lemmatizer.this.type
    Definition Classes
    CanBeLazy
  80. final def setOutputCol(value: String): Lemmatizer.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  81. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  82. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  83. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): LemmatizerModel
    Definition Classes
    Lemmatizer → AnnotatorApproach
  84. 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
  85. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  86. val uid: String
    Definition Classes
    Lemmatizer → Identifiable
  87. 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
  88. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  89. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  90. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  91. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from AnnotatorApproach[LemmatizerModel]

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[LemmatizerModel]

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

Members

Parameter setters

Parameter getters