Packages

class ChunkTokenizerModel extends TokenizerModel

Instantiated model of the ChunkTokenizer. For usage and examples see the documentation of the main class.

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

Instance Constructors

  1. new ChunkTokenizerModel()
  2. new ChunkTokenizerModel(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
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def addSplitChars(v: String): ChunkTokenizerModel.this.type

    One character string to split tokens inside, such as hyphens.

    One character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

    Definition Classes
    TokenizerModel
  11. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  12. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    one to many annotation

    one to many annotation

    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
    ChunkTokenizerModel → TokenizerModel → HasSimpleAnnotate
  13. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  14. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  15. val caseSensitiveExceptions: BooleanParam

    Whether to care for case sensitiveness in exceptions (Default: true)

    Whether to care for case sensitiveness in exceptions (Default: true)

    Definition Classes
    TokenizerModel
  16. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  17. final def clear(param: Param[_]): ChunkTokenizerModel.this.type
    Definition Classes
    Params
  18. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  19. def copy(extra: ParamMap): TokenizerModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  20. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  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. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  25. val exceptions: StringArrayParam

    Words that won't be affected by tokenization rules

    Words that won't be affected by tokenization rules

    Definition Classes
    TokenizerModel
  26. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  27. def explainParams(): String
    Definition Classes
    Params
  28. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  29. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  30. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  31. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  32. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  33. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  34. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  36. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  37. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  38. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  39. def getCaseSensitiveExceptions(value: Boolean): Boolean

    Whether to follow case sensitiveness for matching exceptions in text

    Whether to follow case sensitiveness for matching exceptions in text

    Definition Classes
    TokenizerModel
  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 getExceptions: Array[String]

    Words that won't be affected by tokenization rules

    Words that won't be affected by tokenization rules

    Definition Classes
    TokenizerModel
  43. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  44. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  45. def getMaxLength(value: Int): Int

    Set the maximum allowed length for each token

    Set the maximum allowed length for each token

    Definition Classes
    TokenizerModel
  46. def getMinLength(value: Int): Int

    Set the minimum allowed length for each token

    Set the minimum allowed length for each token

    Definition Classes
    TokenizerModel
  47. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  48. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  49. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  50. def getSplitChars: Array[String]

    List of 1 character string to split tokens inside, such as hyphens.

    List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns

    Definition Classes
    TokenizerModel
  51. def getSplitPattern: String

    List of 1 character string to split tokens inside, such as hyphens.

    List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

    Definition Classes
    TokenizerModel
  52. def getTargetPattern: String

    pattern to grab from text as token candidates.

    pattern to grab from text as token candidates. Defaults \\S+

    Definition Classes
    TokenizerModel
  53. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  54. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  55. def hasParent: Boolean
    Definition Classes
    Model
  56. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  57. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  58. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. val inputAnnotatorTypes: Array[AnnotatorType]

    Output Annotator Type : CHUNK

    Output Annotator Type : CHUNK

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

    Set the maximum allowed length for each token

    Set the maximum allowed length for each token

    Definition Classes
    TokenizerModel
  79. val minLength: IntParam

    Set the minimum allowed length for each token

    Set the minimum allowed length for each token

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

    Output Annotator Type : TOKEN

    Output Annotator Type : TOKEN

    Definition Classes
    ChunkTokenizerModel → TokenizerModel → HasOutputAnnotatorType
  87. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  88. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  89. var parent: Estimator[TokenizerModel]
    Definition Classes
    Model
  90. val rules: StructFeature[RuleFactory]

    rules

    rules

    Definition Classes
    TokenizerModel
  91. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  92. def set[T](feature: StructFeature[T], value: T): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  93. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  94. def set[T](feature: SetFeature[T], value: Set[T]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  95. def set[T](feature: ArrayFeature[T], value: Array[T]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. final def set(paramPair: ParamPair[_]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  97. final def set(param: String, value: Any): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  98. final def set[T](param: Param[T], value: T): ChunkTokenizerModel.this.type
    Definition Classes
    Params
  99. def setCaseSensitiveExceptions(value: Boolean): ChunkTokenizerModel.this.type

    Whether to follow case sensitiveness for matching exceptions in text

    Whether to follow case sensitiveness for matching exceptions in text

    Definition Classes
    TokenizerModel
  100. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. final def setDefault(paramPairs: ParamPair[_]*): ChunkTokenizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. final def setDefault[T](param: Param[T], value: T): ChunkTokenizerModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  106. def setExceptions(value: Array[String]): ChunkTokenizerModel.this.type

    Words that won't be affected by tokenization rules

    Words that won't be affected by tokenization rules

    Definition Classes
    TokenizerModel
  107. final def setInputCols(value: String*): ChunkTokenizerModel.this.type
    Definition Classes
    HasInputAnnotationCols
  108. def setInputCols(value: Array[String]): ChunkTokenizerModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  109. def setLazyAnnotator(value: Boolean): ChunkTokenizerModel.this.type
    Definition Classes
    CanBeLazy
  110. def setMaxLength(value: Int): ChunkTokenizerModel.this.type

    Set the maximum allowed length for each token

    Set the maximum allowed length for each token

    Definition Classes
    TokenizerModel
  111. def setMinLength(value: Int): ChunkTokenizerModel.this.type

    Set the minimum allowed length for each token

    Set the minimum allowed length for each token

    Definition Classes
    TokenizerModel
  112. final def setOutputCol(value: String): ChunkTokenizerModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  113. def setParent(parent: Estimator[TokenizerModel]): TokenizerModel
    Definition Classes
    Model
  114. def setRules(ruleFactory: RuleFactory): ChunkTokenizerModel.this.type

    Rules factory for tokenization

    Rules factory for tokenization

    Definition Classes
    TokenizerModel
  115. def setSplitChars(v: Array[String]): ChunkTokenizerModel.this.type

    List of 1 character string to split tokens inside, such as hyphens.

    List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

    Definition Classes
    TokenizerModel
  116. def setSplitPattern(value: String): ChunkTokenizerModel.this.type

    List of 1 character string to split tokens inside, such as hyphens.

    List of 1 character string to split tokens inside, such as hyphens. Ignored if using infix, prefix or suffix patterns.

    Definition Classes
    TokenizerModel
  117. def setTargetPattern(value: String): ChunkTokenizerModel.this.type

    pattern to grab from text as token candidates.

    pattern to grab from text as token candidates. Defaults \\S+

    Definition Classes
    TokenizerModel
  118. val splitChars: StringArrayParam

    character list used to separate from the inside of tokens

    character list used to separate from the inside of tokens

    Definition Classes
    TokenizerModel
  119. val splitPattern: Param[String]

    pattern to separate from the inside of tokens.

    pattern to separate from the inside of tokens. takes priority over splitChars.

    Definition Classes
    TokenizerModel
  120. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  121. def tag(sentences: Seq[Sentence]): Seq[TokenizedSentence]

    This func generates a Seq of TokenizedSentences from a Seq of Sentences.

    This func generates a Seq of TokenizedSentences from a Seq of Sentences.

    sentences

    to tag

    returns

    Seq of TokenizedSentence objects

    Definition Classes
    TokenizerModel
  122. val targetPattern: Param[String]

    pattern to grab from text as token candidates.

    pattern to grab from text as token candidates. Defaults \\S+

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

Inherited from TokenizerModel

Inherited from HasSimpleAnnotate[TokenizerModel]

Inherited from AnnotatorModel[TokenizerModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[TokenizerModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[TokenizerModel]

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

Parameter getters