ShallowNLPProcessor

Value Members

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

   

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2. final def ##(): Int

   

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

   

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4. def annotate(doc: Document): Document

   

   Definition Classes

   Processor

5. def annotate(text: String, keepText: Boolean): Document

   

   Definition Classes

   Processor

6. def annotateFromSentences(sentences: Iterable[String], keepText: Boolean): Document

   

   Definition Classes

   Processor

7. def annotateFromTokens(sentences: Iterable[Iterable[String]], keepText: Boolean): Document

   

   Definition Classes

   Processor

8. def arrayOrNone[T](b: ArrayBuffer[T])(implicit arg0: ClassTag[T]): Option[Array[T]]

   

9. final def asInstanceOf[T0]: T0

   

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   Any

10. def basicSanityCheck(doc: Document, checkAnnotation: Boolean = true): Option[Annotation]

    

11. lazy val chunker: CRFChunker

    

12. def chunking(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

13. def clone(): AnyRef

    

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    protected[java.lang]

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    @throws( ... )

14. def discourse(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

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

    

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16. def equals(arg0: Any): Boolean

    

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17. def finalize(): Unit

    

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    protected[java.lang]

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    @throws( classOf[java.lang.Throwable] )

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

    

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19. def hashCode(): Int

    

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20. def in(s: String): String

    

21. val internStrings: Boolean

    

22. final def isInstanceOf[T0]: Boolean

    

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    Any

23. def labelSemanticRoles(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

24. def lemmatize(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

25. lazy val lemmatizer: StanfordCoreNLP

    

26. def mkChunker: CRFChunker

    

27. def mkDocument(text: String, keepText: Boolean): Document

    

    Definition Classes

    ShallowNLPProcessor → Processor

28. def mkDocumentFromSentences(sentences: Iterable[String], keepText: Boolean, charactersBetweenSentences: Int = 1): Document

    

    Definition Classes

    ShallowNLPProcessor → Processor

29. def mkDocumentFromTokens(sentences: Iterable[Iterable[String]], keepText: Boolean, charactersBetweenSentences: Int = 1, charactersBetweenTokens: Int = 1): Document

    

    Definition Classes

    ShallowNLPProcessor → Processor

30. def mkLemmatizer: StanfordCoreNLP

    

31. def mkNer: StanfordCoreNLP

    

32. def mkPosTagger: StanfordCoreNLP

    

33. def mkSentence(annotation: CoreMap): Sentence

    

34. def mkTokenizerWithSentenceSplitting: StanfordCoreNLP

    

35. def mkTokenizerWithoutSentenceSplitting: StanfordCoreNLP

    

36. def namedEntitySanityCheck(doc: Document): Option[Annotation]

    

37. final def ne(arg0: AnyRef): Boolean

    

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38. lazy val ner: StanfordCoreNLP

    

39. final def notify(): Unit

    

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40. final def notifyAll(): Unit

    

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41. def parse(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

42. lazy val posTagger: StanfordCoreNLP

    

43. def postprocessTags(annotation: Annotation): Unit

    

    Hook to allow postprocessing of CoreNLP POS tagging *in place*, overwriting original POS tags This is useful for domain-specific corrections

    Hook to allow postprocessing of CoreNLP POS tagging *in place*, overwriting original POS tags This is useful for domain-specific corrections

    annotation

    The CoreNLP annotation

44. def postprocessTokens(sentence: CoreMap): List[CoreLabel]

    

    Attributes

    protected

45. def postprocessTokens(originalTokens: Array[CoreLabel]): Array[CoreLabel]

    

    Hook to allow postprocessing of CoreNLP tokenization This is useful for domain-specific corrections, such as the ones in BioNLPProcessor If you change the tokens, make sure to store them back in the sentence!

    Hook to allow postprocessing of CoreNLP tokenization This is useful for domain-specific corrections, such as the ones in BioNLPProcessor If you change the tokens, make sure to store them back in the sentence!

    originalTokens

    Input CoreNLP sentence

    returns

    The modified tokens

46. def preprocessSentences(origSentences: Iterable[String]): Iterable[String]

    

    Definition Classes

    Processor

47. def preprocessText(origText: String): String

    

    Definition Classes

    Processor

48. def preprocessTokens(origSentences: Iterable[Iterable[String]]): Iterable[Iterable[String]]

    

    Definition Classes

    Processor

49. def recognizeNamedEntities(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

50. def resolveCoreference(doc: Document): Unit

    

    Definition Classes

    ShallowNLPProcessor → Processor

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

    

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52. def tagPartsOfSpeech(doc: Document): Unit

    

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    ShallowNLPProcessor → Processor

53. def toString(): String

    

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54. lazy val tokenizerWithSentenceSplitting: StanfordCoreNLP

    

55. lazy val tokenizerWithoutSentenceSplitting: StanfordCoreNLP

    

56. final def wait(): Unit

    

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57. final def wait(arg0: Long, arg1: Int): Unit

    

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58. final def wait(arg0: Long): Unit

    

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59. val withChunks: Boolean