Object/Class

com.johnsnowlabs.nlp

Annotation

Related Docs: class Annotation | package nlp

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object Annotation extends Serializable

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Serializable, Serializable, AnyRef, Any
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  1. Annotation
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Type Members

  1. case class AnnotationContainer(__annotation: Array[Annotation]) extends Product with Serializable

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
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  3. final def ==(arg0: Any): Boolean

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    Definition Classes
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  4. val EMBEDDINGS: String

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  5. val RESULT: String

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  6. def apply(rawText: String): Annotation

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  7. def apply(row: Row): Annotation

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    This method converts a org.apache.spark.sql.Row into an Annotation

    This method converts a org.apache.spark.sql.Row into an Annotation

    row

    spark row to be converted

    returns

    annotation

  8. final def asInstanceOf[T0]: T0

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    Definition Classes
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  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def collect(dataset: Dataset[Row], column: String, columns: String*): Array[Array[Annotation]]

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  11. def collect(dataset: Dataset[Row], column: String): Array[Array[Annotation]]

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    dataframe collect of a specific annotation column

  12. val dataType: StructType

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    This is spark type of an annotation representing its metadata shape

  13. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
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  14. def equals(arg0: Any): Boolean

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    Definition Classes
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  15. object extractors

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  16. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. def flatten(vSep: String, aSep: String): UserDefinedFunction

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    dataframe annotation flatmap of results into strings

  18. def flattenArray: UserDefinedFunction

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    dataframe annotation flatmap of result values as ArrayType

  19. def flattenArrayMetadata: UserDefinedFunction

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    dataframe annotation flatmap of metadata values as ArrayType

  20. def flattenDetail(vSep: String, aSep: String): UserDefinedFunction

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    dataframe annotation flatmap of results and metadata key values into strings

  21. def getAnnotations(row: Row, colName: String): Seq[Annotation]

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  22. def getAnnotations(row: Row, colNum: Int): Seq[Annotation]

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  23. final def getClass(): Class[_]

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    Definition Classes
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  24. def getColumnByType(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): StructField

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  25. def hashCode(): Int

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    Definition Classes
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  26. final def isInstanceOf[T0]: Boolean

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    Definition Classes
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  27. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
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  28. final def notify(): Unit

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    Definition Classes
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  29. final def notifyAll(): Unit

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    Definition Classes
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  30. def searchCoverage(annotations: Array[Annotation], begin: Int, end: Int): Seq[Annotation]

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  31. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
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  32. def take(dataset: Dataset[Row], column: String, howMany: Int): Array[Array[Annotation]]

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    dataframe take of a specific annotation column

  33. def toString(): String

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    Definition Classes
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  34. final def wait(): Unit

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    Definition Classes
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    Annotations
    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
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    Annotations
    @throws( ... )
  36. final def wait(arg0: Long): Unit

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    Definition Classes
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    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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