cc.factorie.app.nlp.pos

ForwardPosTagger

class ForwardPosTagger extends DocumentAnnotator

A part-of-speech tagger that predicts by greedily labeling each word in sequence. Although it does not use Viterbi, it is surprisingly accurate. It is also fast.

For the Viterbi-based part-of-speech tagger, see ChainPosTagger.

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Instance Constructors

  1. new ForwardPosTagger(url: URL)

  2. new ForwardPosTagger(file: File)

  3. new ForwardPosTagger(stream: InputStream)

  4. new ForwardPosTagger()

Type Members

  1. class FeatureVariable extends BinaryFeatureVectorVariable[String]

  2. class Lemmas extends IndexedSeq[String]

    A special IndexedSeq[String] that will return "null" for indices out of bounds, rather than throwing an error

  3. class SentenceClassifierExample extends optimize.Example

Value Members

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

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

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

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

    Definition Classes
    Any
  6. object FeatureDomain extends CategoricalVectorDomain[String]

  7. object WordData

    Infrastructure for building and remembering a list of training data words that nearly always have the same POS tag.

  8. def accuracy(sentences: Iterable[Sentence]): (Double, Double, Double, Double)

  9. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  10. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. def deserialize(stream: InputStream): Unit

  12. def deserialize(file: File): Unit

  13. def documentAnnotationString(document: Document): String

    How the annotation of this DocumentAnnotator should be printed as extra information after a one-word-per-line (OWPL) format.

    How the annotation of this DocumentAnnotator should be printed as extra information after a one-word-per-line (OWPL) format. If there is no document annotation, return the empty string. Used in Document.owplString.

    Definition Classes
    DocumentAnnotator
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  16. var exampleSetsToPrediction: Boolean

  17. def features(tokens: Seq[Token]): Seq[SparseBinaryTensor1]

  18. def features(token: Token, lemmaIndex: Int, lemmas: Lemmas): SparseBinaryTensor1

  19. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
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    @throws( classOf[java.lang.Throwable] )
  20. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  21. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  22. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  23. def lemmas(tokens: Seq[Token]): Lemmas

    Attributes
    protected
  24. def lemmatize(string: String): String

    Local lemmatizer used for POS features.

    Local lemmatizer used for POS features.

    Attributes
    protected
  25. def mentionAnnotationString(mention: Mention): String

    Definition Classes
    DocumentAnnotator
  26. lazy val model: LinearMulticlassClassifier

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

    Definition Classes
    AnyRef
  28. final def notify(): Unit

    Definition Classes
    AnyRef
  29. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  30. def phraseAnnotationString(phrase: Phrase): String

    Definition Classes
    DocumentAnnotator
  31. def postAttrs: Iterable[Class[_]]

    Definition Classes
    ForwardPosTaggerDocumentAnnotator
  32. def predict(document: Document): Unit

  33. def predict(span: TokenSpan): Unit

  34. def predict(tokens: Seq[Token]): Unit

  35. def prereqAttrs: Iterable[Class[_]]

    Definition Classes
    ForwardPosTaggerDocumentAnnotator
  36. def printAccuracy(sentences: Iterable[Sentence], extraText: String): Unit

  37. def process(s: Sentence): Sentence

  38. def process(d: Document): Document

    Definition Classes
    ForwardPosTaggerDocumentAnnotator
  39. def processParallel(documents: Iterable[Document], nThreads: Int = ...): Iterable[Document]

    Definition Classes
    DocumentAnnotator
  40. def processSequential(documents: Iterable[Document]): Iterable[Document]

    Definition Classes
    DocumentAnnotator
  41. def serialize(stream: OutputStream): Unit

  42. def serialize(filename: String): Unit

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

    Definition Classes
    AnyRef
  44. def test(sentences: Iterable[Sentence]): Unit

  45. def toString(): String

    Definition Classes
    AnyRef → Any
  46. def tokenAnnotationString(token: Token): String

    How the annotation of this DocumentAnnotator should be printed in one-word-per-line (OWPL) format.

    How the annotation of this DocumentAnnotator should be printed in one-word-per-line (OWPL) format. If there is no per-token annotation, return null. Used in Document.owplString.

    Definition Classes
    ForwardPosTaggerDocumentAnnotator
  47. def train(trainSentences: Seq[Sentence], testSentences: Seq[Sentence], lrate: Double = 0.1, decay: Double = 0.01, cutoff: Int = 2, doBootstrap: Boolean = true, useHingeLoss: Boolean = false, numIterations: Int = 5, l1Factor: Double = 0.000001, l2Factor: Double = 0.000001)(implicit random: Random): Unit

  48. final def wait(): Unit

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

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

    Definition Classes
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    @throws( ... )

Inherited from DocumentAnnotator

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