Package 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. This 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	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)	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)	Computes the top k chunk sequences for the specified sentence with the specified pos-tags.
Sequence[]	topKSequences(String[] sentence, String[] tags, double minSequenceScore)	Computes 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)	Starts a training of a ChunkerModel 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

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)

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

Computes 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

Computes 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 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()

Returns an array with the probabilities of the last decoded sequence. The sequence was determined based on the previous call to chunk(String[], String[]).

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,
 ObjectStream<ChunkSample> in,
 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.