opennlp.tools.lemmatizer

## Class LemmatizerME

- java.lang.Object
- - opennlp.tools.lemmatizer.LemmatizerME

- All Implemented Interfaces:
    Lemmatizer

      public class LemmatizerME
      extends Object
      implements Lemmatizer

  A probabilistic lemmatizer. Tries to predict the induced permutation class for each word depending on its surrounding context. Based on Grzegorz Chrupała. 2008. Towards a Machine-Learning Architecture for Lexical Functional Grammar Parsing. PhD dissertation, Dublin City University. http://grzegorz.chrupala.me/papers/phd-single.pdf

- - ### Field Summary

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

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `LemmatizerME(LemmatizerModel model)` Initializes the current instance with the provided model and the default beam size of 3.

  - ### Method Summary

    All Methods Static Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `static String[]` | `decodeLemmas(String[] toks, String[] preds)` Decodes the lemma from the word and the induced lemma class.
    `static String[]` | `encodeLemmas(String[] toks, String[] lemmas)`
    `List<List<String>>` | `lemmatize(List<String> toks, List<String> tags)` Generates a lemma tags for the word and postag returning the result in a list of every possible lemma for each token and postag.
    `String[]` | `lemmatize(String[] toks, String[] tags)` Generates lemmas for the word and postag returning the result in an array.
    `String[][]` | `predictLemmas(int numLemmas, String[] toks, String[] tags)` Predict all possible lemmas (using a default upper bound).
    `String[]` | `predictSES(String[] toks, String[] tags)` Predict Short Edit Script (automatically induced lemma class).
    `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[]` | `topKLemmaClasses(String[] sentence, String[] tags)`
    `Sequence[]` | `topKLemmaClasses(String[] sentence, String[] tags, double minSequenceScore)`
    `Sequence[]` | `topKSequences(String[] sentence, String[] tags)`
    `Sequence[]` | `topKSequences(String[] sentence, String[] tags, double minSequenceScore)`
    `static LemmatizerModel` | `train(String languageCode, ObjectStream<LemmaSample> samples, TrainingParameters trainParams, LemmatizerFactory posFactory)`

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

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

- - ### Field Detail

    - #### LEMMA_NUMBER

          public static final int LEMMA_NUMBER

      See Also:
        Constant Field Values

    - #### DEFAULT_BEAM_SIZE

          public static final int DEFAULT_BEAM_SIZE

      See Also:
        Constant Field Values

  - ### Constructor Detail

    - #### LemmatizerME

          public LemmatizerME(LemmatizerModel model)

      Initializes the current instance with the provided model and the default beam size of 3.
      Parameters:
        `model` - the model

  - ### Method Detail

    - #### lemmatize

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

      Description copied from interface: `Lemmatizer`
      Generates lemmas for the word and postag returning the result in an array.
      Specified by:
        `lemmatize` in interface `Lemmatizer`
      Parameters:
        `toks` - an array of the tokens
        `tags` - an array of the pos tags
      Returns:
        an array of possible lemmas for each token in the sequence.

    - #### lemmatize

          public List<List<String>> lemmatize(List<String> toks,
                                              List<String> tags)

      Description copied from interface: `Lemmatizer`
      Generates a lemma tags for the word and postag returning the result in a list of every possible lemma for each token and postag.
      Specified by:
        `lemmatize` in interface `Lemmatizer`
      Parameters:
        `toks` - an array of the tokens
        `tags` - an array of the pos tags
      Returns:
        a list of every possible lemma for each token in the sequence.

    - #### predictSES

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

      Predict Short Edit Script (automatically induced lemma class).
      Parameters:
        `toks` - the array of tokens
        `tags` - the array of pos tags
      Returns:
        an array containing the lemma classes

    - #### predictLemmas

          public String[][] predictLemmas(int numLemmas,
                                          String[] toks,
                                          String[] tags)

      Predict all possible lemmas (using a default upper bound).
      Parameters:
        `numLemmas` - the default number of lemmas
        `toks` - the tokens
        `tags` - the postags
      Returns:
        a double array containing all posible lemmas for each token and postag pair

    - #### decodeLemmas

          public static String[] decodeLemmas(String[] toks,
                                              String[] preds)

      Decodes the lemma from the word and the induced lemma class.
      Parameters:
        `toks` - the array of tokens
        `preds` - the predicted lemma classes
      Returns:
        the array of decoded lemmas

    - #### encodeLemmas

          public static String[] encodeLemmas(String[] toks,
                                              String[] lemmas)

    - #### topKSequences

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

    - #### topKSequences

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

    - #### 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 `lemmatize`. The specified array should be at least as large as the number of tokens in the previous call to `lemmatize`.
      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 LemmatizerModel train(String languageCode,
                                              ObjectStream<LemmaSample> samples,
                                              TrainingParameters trainParams,
                                              LemmatizerFactory posFactory)
                                       throws IOException

      Throws:
        `IOException`

    - #### topKLemmaClasses

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

    - #### topKLemmaClasses

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

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