Class TokenizerME
- java.lang.Object
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- opennlp.tools.tokenize.TokenizerME
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- All Implemented Interfaces:
Tokenizer
public class TokenizerME extends Object
ATokenizer
for converting raw text into separated tokens. It uses Maximum Entropy to make its decisions. The features are loosely based off of Jeff Reynar's UPenn thesis "Topic Segmentation: Algorithms and Applications.", which is available from his homepage: http://www.cis.upenn.edu/~jcreynar.This implementation needs a statistical model to tokenize a text which reproduces the tokenization observed in the training data used to create the model. The
TokenizerModel
class encapsulates that model and provides methods to create it from the binary representation.A tokenizer instance is not thread-safe. For each thread, one tokenizer must be instantiated which can share one
TokenizerModel
instance to safe memory.To train a new model, the
train(ObjectStream, TokenizerFactory, TrainingParameters)
method can be used.Sample usage:
InputStream modelIn;
...
TokenizerModel model = TokenizerModel(modelIn);
Tokenizer tokenizer = new TokenizerME(model);
String tokens[] = tokenizer.tokenize("A sentence to be tokenized.");- See Also:
Tokenizer
,TokenizerModel
,TokenSample
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Field Summary
Fields Modifier and Type Field Description static Pattern
alphaNumeric
Deprecated.As of release 1.5.2, replaced byFactory.getAlphanumeric(String)
static String
NO_SPLIT
Constant indicates no token split.static String
SPLIT
Constant indicates a token split.
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Constructor Summary
Constructors Constructor Description TokenizerME(String language)
Initializes aTokenizerME
by downloading a default model.TokenizerME(TokenizerModel model)
Instantiates aTokenizerME
with an existingTokenizerModel
.TokenizerME(TokenizerModel model, Factory factory)
Deprecated.useTokenizerFactory
to extend the Tokenizer functionality
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description double[]
getTokenProbabilities()
void
setKeepNewLines(boolean keepNewLines)
Switches whether to keep new lines or not.String[]
tokenize(String s)
Splits a string into its atomic parts.Span[]
tokenizePos(String d)
Tokenizes the string.static TokenizerModel
train(ObjectStream<TokenSample> samples, TokenizerFactory factory, TrainingParameters mlParams)
Trains a model for theTokenizerME
.boolean
useAlphaNumericOptimization()
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Field Detail
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SPLIT
public static final String SPLIT
Constant indicates a token split.- See Also:
- Constant Field Values
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NO_SPLIT
public static final String NO_SPLIT
Constant indicates no token split.- See Also:
- Constant Field Values
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alphaNumeric
@Deprecated public static final Pattern alphaNumeric
Deprecated.As of release 1.5.2, replaced byFactory.getAlphanumeric(String)
Alpha-Numeric Pattern
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Constructor Detail
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TokenizerME
public TokenizerME(String language) throws IOException
Initializes aTokenizerME
by downloading a default model.- Parameters:
language
- The language of the tokenizer.- Throws:
IOException
- Thrown if the model cannot be downloaded or saved.
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TokenizerME
public TokenizerME(TokenizerModel model)
Instantiates aTokenizerME
with an existingTokenizerModel
.- Parameters:
model
- TheTokenizerModel
to be used.
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TokenizerME
@Deprecated public TokenizerME(TokenizerModel model, Factory factory)
Deprecated.useTokenizerFactory
to extend the Tokenizer functionality
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Method Detail
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getTokenProbabilities
public double[] getTokenProbabilities()
- Returns:
- the probabilities associated with the most recent calls to
Tokenizer.tokenize(String)
ortokenizePos(String)
. If not applicable an empty array is returned.
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tokenizePos
public Span[] tokenizePos(String d)
Tokenizes the string.- Parameters:
d
- The string to be tokenized.- Returns:
- A
Span
array containing individual tokens as elements.
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train
public static TokenizerModel train(ObjectStream<TokenSample> samples, TokenizerFactory factory, TrainingParameters mlParams) throws IOException
Trains a model for theTokenizerME
.- Parameters:
samples
- The samples used for the training.factory
- ATokenizerFactory
to get resources from.mlParams
- The machine learningtrain parameters
.- Returns:
- A trained
TokenizerModel
. - Throws:
IOException
- Thrown during IO operations on a temp file which is created during training. Or if reading from theObjectStream
fails.
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useAlphaNumericOptimization
public boolean useAlphaNumericOptimization()
- Returns:
true
if the tokenizer uses alphanumeric optimization,false
otherwise.
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tokenize
public String[] tokenize(String s)
Description copied from interface:Tokenizer
Splits a string into its atomic parts.
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setKeepNewLines
public void setKeepNewLines(boolean keepNewLines)
Switches whether to keep new lines or not.- Parameters:
keepNewLines
-True
if new lines are kept,false
otherwise.
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