Package opennlp.tools.postag

# Class POSTaggerME

java.lang.Object
opennlp.tools.postag.POSTaggerME

All Implemented Interfaces:
  `POSTagger`

public class POSTaggerME extends Object implements POSTagger
A `part-of-speech tagger` implementation that uses maximum entropy.

Tries to predict whether words are nouns, verbs, or any other `POS tags` depending on their surrounding context.

See Also:
  - `POSModel`
  - `POSTagFormat`
  - `POSTagger`

- ## Field Summary

  Fields
  Modifier and Type
  Field
  Description
  `static final int`
  `DEFAULT_BEAM_SIZE`
  The default beam size value is 3.

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `POSTaggerME(String language)`
  Initializes a `POSTaggerME` by downloading a default model for a given `language`.
  `POSTaggerME(String language, POSTagFormat format)`
  Initializes a `POSTaggerME` by downloading a default model for a given `language`.
  `POSTaggerME(POSModel model)`
  Initializes a `POSTaggerME` with the provided `model`.
  `POSTaggerME(POSModel model, POSTagFormat format)`
  Initializes a `POSTaggerME` with the provided `model`.

- ## Method Summary

  Modifier and Type
  Method
  Description
  `static Dictionary`
  `buildNGramDictionary(ObjectStream<POSSample> samples, int cutoff)`
  Constructs a `nGram dictionary` from an `ObjectStream` of samples.
  `String[]`
  `getAllPosTags()`
  `String[]`
  `getOrderedTags(List<String> words, List<String> tags, int index)`
  `String[]`
  `getOrderedTags(List<String> words, List<String> tags, int index, double[] tprobs)`
  `static void`
  `populatePOSDictionary(ObjectStream<POSSample> samples, MutableTagDictionary dict, int cutoff)`
  Populates a `POSDictionary` from an `ObjectStream` of samples.
  `double[]`
  `probs()`
  `void`
  `probs(double[] probs)`
  Populates the specified `probs` array with the probabilities for each tag of the last tagged sentence.
  `String[][]`
  `tag(int numTaggings, String[] sentence)`
  Returns at most the specified `numTaggings` for the specified `sentence`.
  `String[]`
  `tag(String[] sentence)`
  Assigns the sentence of tokens pos tags.
  `String[]`
  `tag(String[] sentence, Object[] additionalContext)`
  Assigns the sentence of tokens pos tags.
  `Sequence[]`
  `topKSequences(String[] sentence)`
  Assigns the sentence the top-k `sequences`.
  `Sequence[]`
  `topKSequences(String[] sentence, Object[] additionalContext)`
  Assigns the sentence the top-k `sequences`.
  `static POSModel`
  `train(String languageCode, ObjectStream<POSSample> samples, TrainingParameters mlParams, POSTaggerFactory posFactory)`
  Starts a training of a `POSModel` with the given parameters.

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

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

- ## Field Details

  - ### DEFAULT_BEAM_SIZE

    public static final int DEFAULT_BEAM_SIZE
    The default beam size value is 3.
    See Also:
      - Constant Field Values

- ## Constructor Details

  - ### POSTaggerME

    public POSTaggerME(String language) throws IOException
    Initializes a `POSTaggerME` by downloading a default model for a given `language`.
    Parameters:
      `language` - An ISO conform language code.
    Throws:
      `IOException` - Thrown if the model could not be downloaded or saved.

  - ### POSTaggerME

    public POSTaggerME(String language, POSTagFormat format) throws IOException
    Initializes a `POSTaggerME` by downloading a default model for a given `language`.
    Parameters:
      `language` - An ISO conform language code.
      `format` - A valid `POSTagFormat`.
    Throws:
      `IOException` - Thrown if the model could not be downloaded or saved.

  - ### POSTaggerME

    public POSTaggerME(POSModel model)
    Initializes a `POSTaggerME` with the provided `model`.
    Parameters:
      `model` - A valid `POSModel`.

  - ### POSTaggerME

    public POSTaggerME(POSModel model, POSTagFormat format)
    Initializes a `POSTaggerME` with the provided `model`.
    Parameters:
      `model` - A valid `POSModel`.
      `format` - A valid `POSTagFormat`.

- ## Method Details

  - ### getAllPosTags

    public String[] getAllPosTags()
    Returns:
      Retrieves an array of all possible part-of-speech tags from the tagger.

  - ### tag

    public String[] tag(String[] sentence)
    Assigns the sentence of tokens pos tags.
    Specified by:
      `tag` in interface `POSTagger`
    Parameters:
      `sentence` - The sentence of tokens to be tagged.
    Returns:
      An array of pos tags for each token provided in `sentence`.

  - ### tag

    public String[] tag(String[] sentence, Object[] additionalContext)
    Assigns the sentence of tokens pos tags.
    Specified by:
      `tag` in interface `POSTagger`
    Parameters:
      `sentence` - The sentence of tokens to be tagged.
      `additionalContext` - The context to provide additional information with.
    Returns:
      An array of pos tags for each token provided in `sentence`.

  - ### tag

    public String[][] tag(int numTaggings, String[] sentence)
    Returns at most the specified `numTaggings` for the specified `sentence`.
    Parameters:
      `numTaggings` - The number of tagging to be returned.
      `sentence` - An array of tokens which make up a sentence.
    Returns:
      At most the specified number of taggings for the specified `sentence`.

  - ### topKSequences

    public Sequence[] topKSequences(String[] sentence)
    Assigns the sentence the top-k `sequences`.
    Specified by:
      `topKSequences` in interface `POSTagger`
    Parameters:
      `sentence` - The sentence of tokens to be tagged.
    Returns:
      An array of `sequences` for each token provided in `sentence`.

  - ### topKSequences

    public Sequence[] topKSequences(String[] sentence, Object[] additionalContext)
    Assigns the sentence the top-k `sequences`.
    Specified by:
      `topKSequences` in interface `POSTagger`
    Parameters:
      `sentence` - The sentence of tokens to be tagged.
      `additionalContext` - The context to provide additional information with.
    Returns:
      An array of `sequences` for each token provided in `sentence`.

  - ### probs

    public void probs(double[] probs)
    Populates the specified `probs` array with the probabilities for each tag of the last tagged sentence.
    Parameters:
      `probs` - An array to put the probabilities into.

  - ### probs

    public double[] probs()
    Returns:
      An array with the probabilities for each tag of the last tagged sentence.

  - ### getOrderedTags

    public String[] getOrderedTags(List<String> words, List<String> tags, int index)

  - ### getOrderedTags

    public String[] getOrderedTags(List<String> words, List<String> tags, int index, double[] tprobs)

  - ### train

    public static POSModel train(String languageCode, ObjectStream<POSSample> samples, TrainingParameters mlParams, POSTaggerFactory posFactory) throws IOException
    Starts a training of a `POSModel` with the given parameters.
    Parameters:
      `languageCode` - The ISO language code to train the model. Must not be `null`.
      `samples` - The `ObjectStream` of `POSSample` used as input for training.
      `mlParams` - The `TrainingParameters` for the context of the training process.
      `posFactory` - The `POSTaggerFactory` for creating related objects as defined via `mlParams`.
    Returns:
      A valid, trained `POSModel` instance.
    Throws:
      `IOException` - Thrown if IO errors occurred.

  - ### buildNGramDictionary

    public static Dictionary buildNGramDictionary(ObjectStream<POSSample> samples, int cutoff) throws IOException
    Constructs a `nGram dictionary` from an `ObjectStream` of samples.
    Parameters:
      `samples` - The `ObjectStream` to process.
      `cutoff` - A non-negative cut-off value.
    Returns:
      A valid `Dictionary` instance holding nGrams.
    Throws:
      `IOException` - Thrown if IO errors occurred during dictionary construction.

  - ### populatePOSDictionary

    public static void populatePOSDictionary(ObjectStream<POSSample> samples, MutableTagDictionary dict, int cutoff) throws IOException
    Populates a `POSDictionary` from an `ObjectStream` of samples.
    Parameters:
      `samples` - The `ObjectStream` to process.
      `dict` - The `MutableTagDictionary` to use during population.
      `cutoff` - A non-negative cut-off value.
    Throws:
      `IOException` - Thrown if IO errors occurred during dictionary construction.