Packages

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

Annotator that detects sentence boundaries using any provided approach.

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 Spark NLP Workshop.

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")

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

val data = Seq("This is my first sentence. This my second. How 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
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
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
  1. Hide All
  2. Show All
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
    SentenceDetectorAnnotatorModel
  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
    SentenceDetectorHasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Definition Classes
    SentenceDetectorAnnotatorModel
  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. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. 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
  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. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  26. def explainParams(): String
    Definition Classes
    Params
  27. 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
  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. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  40. def getCustomBounds: Array[String]

    Custom sentence separator text

    Custom sentence separator text

    Definition Classes
    SentenceDetectorParams
  41. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. 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
  43. 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
  44. def getInputCols: Array[String]

    returns

    input annotations columns currently used

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

    Get the maximum allowed length for each sentence

    Get the maximum allowed length for each sentence

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

    Get the minimum allowed length for each sentence

    Get the minimum allowed length for each sentence

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

    Gets annotation column name going to generate

    Gets annotation column name going to generate

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

    Length at which sentences will be forcibly split

    Length at which sentences will be forcibly split

    Definition Classes
    SentenceDetectorParams
  52. 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
  53. 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
  54. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  55. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  56. def hasParent: Boolean
    Definition Classes
    Model
  57. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  58. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  59. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. val inputAnnotatorTypes: Array[AnnotatorType]

    Input annotator type : DOCUMENT

    Input annotator type : DOCUMENT

    Definition Classes
    SentenceDetectorHasInputAnnotationCols
  61. 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
  62. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  63. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  64. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  65. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  66. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  67. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  68. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  75. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. 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
  80. 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
  81. lazy val model: PragmaticMethod
  82. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  83. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  84. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  85. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  86. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  87. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  88. val outputAnnotatorType: AnnotatorType

    Output annotator type : DOCUMENT

    Output annotator type : DOCUMENT

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

    Custom sentence separator text

    Custom sentence separator text

    Definition Classes
    SentenceDetectorParams
  101. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. final def setDefault(paramPairs: ParamPair[_]*): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    Params
  106. final def setDefault[T](param: Param[T], value: T): SentenceDetector.this.type
    Attributes
    protected
    Definition Classes
    Params
  107. 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
  108. 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
  109. final def setInputCols(value: String*): SentenceDetector.this.type
    Definition Classes
    HasInputAnnotationCols
  110. 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
  111. def setLazyAnnotator(value: Boolean): SentenceDetector.this.type
    Definition Classes
    CanBeLazy
  112. 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
  113. 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
  114. final def setOutputCol(value: String): SentenceDetector.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  115. def setParent(parent: Estimator[SentenceDetector]): SentenceDetector
    Definition Classes
    Model
  116. 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
  117. 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
  118. 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
  119. 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
  120. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  121. def tag(document: String): Array[Sentence]
  122. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  123. 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
  124. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  125. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  126. 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
  127. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  128. def truncateSentence(sentence: String, maxLength: Int): Array[String]
    Definition Classes
    SentenceDetectorParams
  129. val uid: String
    Definition Classes
    SentenceDetector → Identifiable
  130. val useAbbrevations: BooleanParam

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

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

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

Inherited from SentenceDetectorParams

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