cc.factorie.app.nlp.pos.ForwardPosTagger

WordData

object WordData

Infrastructure for building and remembering a list of training data words that nearly always have the same POS tag. Used as cheap "stacked learning" features when looking-ahead to words not yet predicted by this POS tagger. The key into the ambiguityClasses is app.strings.replaceDigits().toLowerCase

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  6. val ambiguityClassThreshold: Double

  7. val ambiguityClasses: Map[String, String]

  8. final def asInstanceOf[T0]: T0

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  9. def clone(): AnyRef

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  10. def computeAmbiguityClasses(tokens: Iterable[Token]): Unit

  11. def computeWordFormsByDocumentFrequency(tokens: Iterable[Token], cutoff: Integer, numToksPerDoc: Int): Unit

  12. var docWordCounts: Map[String, Int]

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

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  14. def equals(arg0: Any): Boolean

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  15. def finalize(): Unit

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

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

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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  22. val sureTokenThreshold: Int

  23. val sureTokens: Map[String, Int]

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

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  25. def toString(): String

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  26. final def wait(): Unit

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

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  29. val wordInclusionThreshold: Int

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