Packages

class SentenceDetector extends AnnotatorModel[SentenceDetector] with HasSimpleAnnotate[SentenceDetector] with SentenceDetectorParams

Annotator that detects sentence boundaries using regular expressions.

The following characters are checked as sentence boundaries:

  1. Lists ("(i), (ii)", "(a), (b)", "1., 2.")
  2. Numbers
  3. Abbreviations
  4. Punctuations
  5. Multiple Periods
  6. Geo-Locations/Coordinates ("N°. 1026.253.553.")
  7. Ellipsis ("...")
  8. In-between punctuations
  9. Quotation marks
  10. Exclamation Points
  11. Basic Breakers (".", ";")

For the explicit regular expressions used for detection, refer to source of https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/main/scala/com/johnsnowlabs/nlp/annotators/sbd/pragmatic/PragmaticContentFormatter.scala.

To add additional custom bounds, the parameter customBounds can be set with an array:

val sentence = new SentenceDetector()
  .setInputCols("document")
  .setOutputCol("sentence")
  .setCustomBounds(Array("\n\n"))

If only the custom bounds should be used, then the parameter useCustomBoundsOnly should be set to true.

Each extracted sentence can be returned in an Array or exploded to separate rows, if explodeSentences is set to true.

For extended examples of usage, see the https://github.com/JohnSnowLabs/spark-nlp/blob/master/examples/python/annotation/text/english/sentence-detection/SentenceDetector_advanced_examples.ipynb.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotator.SentenceDetector
import org.apache.spark.ml.Pipeline

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

val sentence = new SentenceDetector()
  .setInputCols("document")
  .setOutputCol("sentence")
  .setCustomBounds(Array("\n\n"))

val pipeline = new Pipeline().setStages(Array(
  documentAssembler,
  sentence
))

val data = Seq("This is my first sentence. This my second.\n\nHow about a third?").toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("explode(sentence) as sentences").show(false)
+------------------------------------------------------------------+
|sentences                                                         |
+------------------------------------------------------------------+
|[document, 0, 25, This is my first sentence., [sentence -> 0], []]|
|[document, 27, 41, This my second., [sentence -> 1], []]          |
|[document, 43, 60, How about a third?, [sentence -> 2], []]       |
+------------------------------------------------------------------+
See also

SentenceDetectorDLModel for pretrained models

Linear Supertypes
SentenceDetectorParams, HasSimpleAnnotate[SentenceDetector], AnnotatorModel[SentenceDetector], CanBeLazy, RawAnnotator[SentenceDetector], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[SentenceDetector], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SentenceDetector
  2. SentenceDetectorParams
  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 SentenceDetector()
  2. new SentenceDetector(uid: String)

    uid

    internal constructor requirement for serialization of params

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

    Uses the model interface to prepare the context and extract the boundaries

    Uses the model interface to prepare the context and extract the boundaries

    annotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    One to many annotation relationship depending on how many sentences there are in the document

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

    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. val customBounds: StringArrayParam

    Characters used to explicitly mark sentence bounds (Default: None)

    Characters used to explicitly mark sentence bounds (Default: None)

    Definition Classes
    SentenceDetectorParams
  20. val customBoundsStrategy: Param[String]

    How to return matched custom bounds (Default: none).

    How to return matched custom bounds (Default: none). Will have no effect if no custom bounds are used. Possible values are:

    • "none" - Will not return the matched bound
    • "prepend" - Prepends a sentence break to the match
    • "append" - Appends a sentence break to the match
    Definition Classes
    SentenceDetectorParams
  21. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  22. val detectLists: BooleanParam

    Whether take lists into consideration at sentence detection (Default: true)

    Whether take lists into consideration at sentence detection (Default: true)

    Definition Classes
    SentenceDetectorParams
  23. 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
  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 explodeSentences: BooleanParam

    Whether to explode each sentence into a different row, for better parallelization (Default: false)

    Whether to explode each sentence into a different row, for better parallelization (Default: false)

    Definition Classes
    SentenceDetectorParams
  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. def getCustomBounds: Array[String]

    Custom sentence separator text

    Custom sentence separator text

    Definition Classes
    SentenceDetectorParams
  42. def getCustomBoundsStrategy: String

    Gets how to return matched custom bounds (Default: none).

    Gets how to return matched custom bounds (Default: none).

    Definition Classes
    SentenceDetectorParams
  43. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  44. def getDetectLists: Boolean

    Whether to take lists into consideration at sentence detection.

    Whether to take lists into consideration at sentence detection. Defaults to true.

    Definition Classes
    SentenceDetectorParams
  45. def getExplodeSentences: Boolean

    Whether to split sentences into different Dataset rows.

    Whether to split sentences into different Dataset rows. Useful for higher parallelism in fat rows. Defaults to false.

    Definition Classes
    SentenceDetectorParams
  46. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  47. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  48. def getMaxLength(value: Int): Int

    Get the maximum allowed length for each sentence

    Get the maximum allowed length for each sentence

    Definition Classes
    SentenceDetectorParams
  49. def getMinLength(value: Int): Int

    Get the minimum allowed length for each sentence

    Get the minimum allowed length for each sentence

    Definition Classes
    SentenceDetectorParams
  50. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  51. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  52. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  53. def getSplitLength: Int

    Length at which sentences will be forcibly split

    Length at which sentences will be forcibly split

    Definition Classes
    SentenceDetectorParams
  54. def getUseAbbreviations: Boolean

    Whether to consider abbreviation strategies for better accuracy but slower performance.

    Whether to consider abbreviation strategies for better accuracy but slower performance. Defaults to true.

    Definition Classes
    SentenceDetectorParams
  55. def getUseCustomBoundsOnly: Boolean

    Use only custom bounds without considering those of Pragmatic Segmenter.

    Use only custom bounds without considering those of Pragmatic Segmenter. Defaults to false. Needs customBounds.

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

    Input annotator type : DOCUMENT

    Input annotator type : DOCUMENT

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

    Set the maximum allowed length for each sentence (Ignored if not set)

    Set the maximum allowed length for each sentence (Ignored if not set)

    Definition Classes
    SentenceDetectorParams
  82. val minLength: IntParam

    Set the minimum allowed length for each sentence (Default: 0)

    Set the minimum allowed length for each sentence (Default: 0)

    Definition Classes
    SentenceDetectorParams
  83. lazy val model: PragmaticMethod
  84. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  85. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  86. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  87. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  88. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  89. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  90. val outputAnnotatorType: AnnotatorType

    Output annotator type : DOCUMENT

    Output annotator type : DOCUMENT

    Definition Classes
    SentenceDetector → HasOutputAnnotatorType
  91. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  92. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  93. var parent: Estimator[SentenceDetector]
    Definition Classes
    Model
  94. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  95. def set[T](feature: StructFeature[T], value: T): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def set[T](feature: SetFeature[T], value: Set[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  98. def set[T](feature: ArrayFeature[T], value: Array[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. final def set(paramPair: ParamPair[_]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    Params
  100. final def set(param: String, value: Any): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    Params
  101. final def set[T](param: Param[T], value: T): SentenceDetector.this.type
    Definition Classes
    Params
  102. def setCustomBounds(value: Array[String]): SentenceDetector.this.type

    Custom sentence separator text

    Custom sentence separator text

    Definition Classes
    SentenceDetectorParams
  103. def setCustomBoundsStrategy(value: String): SentenceDetector.this.type

    Sets how to return matched custom bounds (Default: none).

    Sets how to return matched custom bounds (Default: none). Will have no effect if no custom bounds are used. Possible values are:

    • "none" - Will not return the matched bound
    • "prepend" - Prepends a sentence break to the match
    • "append" - Appends a sentence break to the match
    Definition Classes
    SentenceDetectorParams
  104. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  107. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. final def setDefault(paramPairs: ParamPair[_]*): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    Params
  109. final def setDefault[T](param: Param[T], value: T): SentenceDetector.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  110. def setDetectLists(value: Boolean): SentenceDetector.this.type

    Whether to take lists into consideration at sentence detection.

    Whether to take lists into consideration at sentence detection. Defaults to true.

    Definition Classes
    SentenceDetectorParams
  111. def setExplodeSentences(value: Boolean): SentenceDetector.this.type

    Whether to split sentences into different Dataset rows.

    Whether to split sentences into different Dataset rows. Useful for higher parallelism in fat rows. Defaults to false.

    Definition Classes
    SentenceDetectorParams
  112. final def setInputCols(value: String*): SentenceDetector.this.type
    Definition Classes
    HasInputAnnotationCols
  113. def setInputCols(value: Array[String]): SentenceDetector.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  114. def setLazyAnnotator(value: Boolean): SentenceDetector.this.type
    Definition Classes
    CanBeLazy
  115. def setMaxLength(value: Int): SentenceDetector.this.type

    Set the maximum allowed length for each sentence

    Set the maximum allowed length for each sentence

    Definition Classes
    SentenceDetectorParams
  116. def setMinLength(value: Int): SentenceDetector.this.type

    Set the minimum allowed length for each sentence

    Set the minimum allowed length for each sentence

    Definition Classes
    SentenceDetectorParams
  117. final def setOutputCol(value: String): SentenceDetector.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  118. def setParent(parent: Estimator[SentenceDetector]): SentenceDetector
    Definition Classes
    Model
  119. def setSplitLength(value: Int): SentenceDetector.this.type

    Length at which sentences will be forcibly split

    Length at which sentences will be forcibly split

    Definition Classes
    SentenceDetectorParams
  120. def setUseAbbreviations(value: Boolean): SentenceDetector.this.type

    Whether to consider abbreviation strategies for better accuracy but slower performance.

    Whether to consider abbreviation strategies for better accuracy but slower performance. Defaults to true.

    Definition Classes
    SentenceDetectorParams
  121. def setUseCustomBoundsOnly(value: Boolean): SentenceDetector.this.type

    Use only custom bounds without considering those of Pragmatic Segmenter.

    Use only custom bounds without considering those of Pragmatic Segmenter. Defaults to false. Needs customBounds.

    Definition Classes
    SentenceDetectorParams
  122. val splitLength: IntParam

    Length at which sentences will be forcibly split (Ignored if not set)

    Length at which sentences will be forcibly split (Ignored if not set)

    Definition Classes
    SentenceDetectorParams
  123. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  124. def tag(document: String): Array[Sentence]
  125. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  126. 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
  127. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  128. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  129. 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
  130. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  131. def truncateSentence(sentence: String, maxLength: Int): Array[String]
    Definition Classes
    SentenceDetectorParams
  132. val uid: String
    Definition Classes
    SentenceDetector → Identifiable
  133. val useAbbrevations: BooleanParam

    Whether to apply abbreviations at sentence detection (Default: true)

    Whether to apply abbreviations at sentence detection (Default: true)

    Definition Classes
    SentenceDetectorParams
  134. val useCustomBoundsOnly: BooleanParam

    Whether to only utilize custom bounds for sentence detection (Default: false)

    Whether to only utilize custom bounds for sentence detection (Default: false)

    Definition Classes
    SentenceDetectorParams
  135. 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
  136. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  137. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  138. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  139. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  140. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from SentenceDetectorParams

Inherited from HasSimpleAnnotate[SentenceDetector]

Inherited from AnnotatorModel[SentenceDetector]

Inherited from CanBeLazy

Inherited from RawAnnotator[SentenceDetector]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[SentenceDetector]

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