Class ChunkerME

java.lang.Object

opennlp.tools.chunker.ChunkerME

All Implemented Interfaces:

opennlp.tools.chunker.Chunker, opennlp.tools.ml.Probabilistic

public class ChunkerME
extends Object
implements opennlp.tools.chunker.Chunker, opennlp.tools.ml.Probabilistic

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

See Also:

• Chunker
• Probabilistic

Field Summary

Fields

Modifier and Type	Field	Description
static final int	DEFAULT_BEAM_SIZE

Constructor Summary

Constructors

Constructor	Description
ChunkerME(String language)	Initializes a Chunker by downloading a default model.
ChunkerME(ChunkerModel model)	Initializes a Chunker with the specified ChunkerModel.

Method Summary

Modifier and Type	Method	Description
String[]	chunk(String[] toks, String[] tags)
opennlp.tools.util.Span[]	chunkAsSpans(String[] toks, String[] tags)
double[]	probs()	The sequence was determined based on the previous call to chunk(String[], String[]).
void	probs(double[] probs)	Populates the specified array with the probabilities of the last decoded sequence.
opennlp.tools.util.Sequence[]	topKSequences(String[] sentence, String[] tags)
opennlp.tools.util.Sequence[]	topKSequences(String[] sentence, String[] tags, double minSequenceScore)
static ChunkerModel	train(String lang, opennlp.tools.util.ObjectStream<opennlp.tools.chunker.ChunkSample> in, opennlp.tools.util.TrainingParameters mlParams, ChunkerFactory factory)	Starts a training of a ChunkerModel with the given parameters.

Methods inherited from class Object

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

Field Details

DEFAULT_BEAM_SIZE

public static final int DEFAULT_BEAM_SIZE

See Also:

• Constant Field Values

Constructor Details

ChunkerME

public ChunkerME(String language)
          throws IOException

Initializes a Chunker by downloading a default model.

Parameters:

language - The language of the model.

Throws:

IOException - Thrown if the model cannot be downloaded or saved.

ChunkerME

public ChunkerME(ChunkerModel model)

Initializes a Chunker with the specified ChunkerModel. The DEFAULT_BEAM_SIZE is used.

Parameters:

model - A valid model instance.

Method Details

chunk

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

Specified by:

chunk in interface opennlp.tools.chunker.Chunker

chunkAsSpans

public opennlp.tools.util.Span[] chunkAsSpans(String[] toks,
 String[] tags)

Specified by:

chunkAsSpans in interface opennlp.tools.chunker.Chunker

topKSequences

public opennlp.tools.util.Sequence[] topKSequences(String[] sentence,
 String[] tags)

Specified by:

topKSequences in interface opennlp.tools.chunker.Chunker

topKSequences

public opennlp.tools.util.Sequence[] topKSequences(String[] sentence,
 String[] tags,
 double minSequenceScore)

Specified by:

topKSequences in interface opennlp.tools.chunker.Chunker

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 number 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()

The sequence was determined based on the previous call to chunk(String[], String[]).

Specified by:

probs in interface opennlp.tools.ml.Probabilistic

Returns:

An array with the same number of probabilities as tokens when chunk(String[], String[]) was last called.

train

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

Starts a training of a ChunkerModel with the given parameters.

Parameters:

lang - The ISO conform language code.

in - The ObjectStream of ChunkSample used as input for training.

mlParams - The TrainingParameters for the context of the training.

factory - The ChunkerFactory for creating related objects defined via mlParams.

Returns:

A valid, trained ChunkerModel instance.

Throws:

IOException - Thrown if IO errors occurred.

IllegalArgumentException - Thrown if the specified TrainerFactory.TrainerType is not supported.