opennlp.tools.chunker

## Class ChunkerME

- java.lang.Object
- - opennlp.tools.chunker.ChunkerME

- All Implemented Interfaces:
    Chunker

      public class ChunkerME
      extends Object
      implements Chunker

  The class represents a maximum-entropy-based chunker. Such a chunker can be used to find flat structures based on sequence inputs such as noun phrases or named entities.

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static int` | `DEFAULT_BEAM_SIZE`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `ChunkerME(ChunkerModel model)` Initializes the current instance with the specified model.

  - ### Method Summary

    All Methods Static Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `String[]` | `chunk(String[] toks, String[] tags)` Generates chunk tags for the given sequence returning the result in an array.
    `Span[]` | `chunkAsSpans(String[] toks, String[] tags)` Generates tagged chunk spans for the given sequence returning the result in a span array.
    `double[]` | `probs()` Returns an array with the probabilities of the last decoded sequence.
    `void` | `probs(double[] probs)` Populates the specified array with the probabilities of the last decoded sequence.
    `Sequence[]` | `topKSequences(String[] sentence, String[] tags)` Returns the top k chunk sequences for the specified sentence with the specified pos-tags
    `Sequence[]` | `topKSequences(String[] sentence, String[] tags, double minSequenceScore)` Returns the top k chunk sequences for the specified sentence with the specified pos-tags
    `static ChunkerModel` | `train(String lang, ObjectStream<ChunkSample> in, TrainingParameters mlParams, ChunkerFactory factory)`

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Field Detail

    - #### DEFAULT_BEAM_SIZE

          public static final int DEFAULT_BEAM_SIZE

      See Also:
        Constant Field Values

  - ### Constructor Detail

    - #### ChunkerME

          public ChunkerME(ChunkerModel model)

      Initializes the current instance with the specified model. The default beam size is used.
      Parameters:
        `model` -

  - ### Method Detail

    - #### chunk

          public String[] chunk(String[] toks,
                                String[] tags)

      Description copied from interface: `Chunker`
      Generates chunk tags for the given sequence returning the result in an array.
      Specified by:
        `chunk` in interface `Chunker`
      Parameters:
        `toks` - an array of the tokens or words of the sequence.
        `tags` - an array of the pos tags of the sequence.
      Returns:
        an array of chunk tags for each token in the sequence.

    - #### chunkAsSpans

          public Span[] chunkAsSpans(String[] toks,
                                     String[] tags)

      Description copied from interface: `Chunker`
      Generates tagged chunk spans for the given sequence returning the result in a span array.
      Specified by:
        `chunkAsSpans` in interface `Chunker`
      Parameters:
        `toks` - an array of the tokens or words of the sequence.
        `tags` - an array of the pos tags of the sequence.
      Returns:
        an array of spans with chunk tags for each chunk in the sequence.

    - #### topKSequences

          public Sequence[] topKSequences(String[] sentence,
                                          String[] tags)

      Description copied from interface: `Chunker`
      Returns the top k chunk sequences for the specified sentence with the specified pos-tags
      Specified by:
        `topKSequences` in interface `Chunker`
      Parameters:
        `sentence` - The tokens of the sentence.
        `tags` - The pos-tags for the specified sentence.
      Returns:
        the top k chunk sequences for the specified sentence.

    - #### topKSequences

          public Sequence[] topKSequences(String[] sentence,
                                          String[] tags,
                                          double minSequenceScore)

      Description copied from interface: `Chunker`
      Returns the top k chunk sequences for the specified sentence with the specified pos-tags
      Specified by:
        `topKSequences` in interface `Chunker`
      Parameters:
        `sentence` - The tokens of the sentence.
        `tags` - The pos-tags for the specified sentence.
        `minSequenceScore` - A lower bound on the score of a returned sequence.
      Returns:
        the top k chunk sequences for the specified sentence.

    - #### probs

          public void probs(double[] probs)

      Populates the specified array with the probabilities of the last decoded sequence. The sequence was determined based on the previous call to `chunk`. The specified array should be at least as large as the numbe of tokens in the previous call to `chunk`.
      Parameters:
        `probs` - An array used to hold the probabilities of the last decoded sequence.

    - #### probs

          public double[] probs()

      Returns an array with the probabilities of the last decoded sequence. The sequence was determined based on the previous call to `chunk`.
      Returns:
        An array with the same number of probabilities as tokens were sent to `chunk` when it was last called.

    - #### train

          public static ChunkerModel train(String lang,
                                           ObjectStream<ChunkSample> in,
                                           TrainingParameters mlParams,
                                           ChunkerFactory factory)
                                    throws IOException

      Throws:
        `IOException`

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