Package opennlp.tools.postag
Class POSTaggerME
java.lang.Object
opennlp.tools.postag.POSTaggerME
- All Implemented Interfaces:
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:
-
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final intThe default beam size value is 3. -
Constructor Summary
ConstructorsConstructorDescriptionPOSTaggerME(String language) Initializes aPOSTaggerMEby downloading a default model for a givenlanguage.POSTaggerME(String language, POSTagFormat format) Initializes aPOSTaggerMEby downloading a default model for a givenlanguage.POSTaggerME(POSModel model) Initializes aPOSTaggerMEwith the providedmodel.POSTaggerME(POSModel model, POSTagFormat format) Initializes aPOSTaggerMEwith the providedmodel. -
Method Summary
Modifier and TypeMethodDescriptionstatic DictionarybuildNGramDictionary(ObjectStream<POSSample> samples, int cutoff) Constructs anGram dictionaryfrom anObjectStreamof samples.String[]String[]getOrderedTags(List<String> words, List<String> tags, int index) String[]getOrderedTags(List<String> words, List<String> tags, int index, double[] tprobs) static voidpopulatePOSDictionary(ObjectStream<POSSample> samples, MutableTagDictionary dict, int cutoff) Populates aPOSDictionaryfrom anObjectStreamof samples.double[]probs()voidprobs(double[] probs) Populates the specifiedprobsarray with the probabilities for each tag of the last tagged sentence.String[][]Returns at most the specifiednumTaggingsfor the specifiedsentence.String[]Assigns the sentence of tokens pos tags.String[]Assigns the sentence of tokens pos tags.Sequence[]topKSequences(String[] sentence) Assigns the sentence the top-ksequences.Sequence[]topKSequences(String[] sentence, Object[] additionalContext) Assigns the sentence the top-ksequences.static POSModeltrain(String languageCode, ObjectStream<POSSample> samples, TrainingParameters mlParams, POSTaggerFactory posFactory) Starts a training of aPOSModelwith the given parameters.
-
Field Details
-
DEFAULT_BEAM_SIZE
public static final int DEFAULT_BEAM_SIZEThe default beam size value is 3.- See Also:
-
-
Constructor Details
-
POSTaggerME
Initializes aPOSTaggerMEby downloading a default model for a givenlanguage.- Parameters:
language- An ISO conform language code.- Throws:
IOException- Thrown if the model could not be downloaded or saved.
-
POSTaggerME
Initializes aPOSTaggerMEby downloading a default model for a givenlanguage.- Parameters:
language- An ISO conform language code.format- A validPOSTagFormat.- Throws:
IOException- Thrown if the model could not be downloaded or saved.
-
POSTaggerME
Initializes aPOSTaggerMEwith the providedmodel.- Parameters:
model- A validPOSModel.
-
POSTaggerME
Initializes aPOSTaggerMEwith the providedmodel.- Parameters:
model- A validPOSModel.format- A validPOSTagFormat.
-
-
Method Details
-
getAllPosTags
- Returns:
- Retrieves an array of all possible part-of-speech tags from the tagger.
-
tag
Assigns the sentence of tokens pos tags. -
tag
Assigns the sentence of tokens pos tags. -
tag
Returns at most the specifiednumTaggingsfor the specifiedsentence.- 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
Assigns the sentence the top-ksequences.- Specified by:
topKSequencesin interfacePOSTagger- Parameters:
sentence- The sentence of tokens to be tagged.- Returns:
- An array of
sequencesfor each token provided insentence.
-
topKSequences
Assigns the sentence the top-ksequences.- Specified by:
topKSequencesin interfacePOSTagger- Parameters:
sentence- The sentence of tokens to be tagged.additionalContext- The context to provide additional information with.- Returns:
- An array of
sequencesfor each token provided insentence.
-
probs
public void probs(double[] probs) Populates the specifiedprobsarray 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
-
getOrderedTags
-
train
public static POSModel train(String languageCode, ObjectStream<POSSample> samples, TrainingParameters mlParams, POSTaggerFactory posFactory) throws IOException Starts a training of aPOSModelwith the given parameters.- Parameters:
languageCode- The ISO language code to train the model. Must not benull.samples- TheObjectStreamofPOSSampleused as input for training.mlParams- TheTrainingParametersfor the context of the training process.posFactory- ThePOSTaggerFactoryfor creating related objects as defined viamlParams.- Returns:
- A valid, trained
POSModelinstance. - Throws:
IOException- Thrown if IO errors occurred.
-
buildNGramDictionary
public static Dictionary buildNGramDictionary(ObjectStream<POSSample> samples, int cutoff) throws IOException Constructs anGram dictionaryfrom anObjectStreamof samples.- Parameters:
samples- TheObjectStreamto process.cutoff- A non-negative cut-off value.- Returns:
- A valid
Dictionaryinstance 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 aPOSDictionaryfrom anObjectStreamof samples.- Parameters:
samples- TheObjectStreamto process.dict- TheMutableTagDictionaryto use during population.cutoff- A non-negative cut-off value.- Throws:
IOException- Thrown if IO errors occurred during dictionary construction.
-