Deprecated API

Contents

• Deprecated Interfaces
• Deprecated Classes
• Deprecated Fields
• Deprecated Methods
• Deprecated Constructors
• Deprecated Enum Constants

Deprecated Interfaces

Interface and Description
opennlp.tools.util.featuregen.FeatureGeneratorFactory do not use this interface, will be removed!

Deprecated Classes

Class and Description
opennlp.tools.sentdetect.AbstractEndOfSentenceScanner use DefaultEndOfSentenceScanner instead
opennlp.tools.util.model.ClassSerializer
opennlp.tools.util.featuregen.FastTokenClassFeatureGenerator Use TokenClassFeatureGenerator instead!
opennlp.tools.util.model.FeatureGeneratorFactorySerializer
opennlp.tools.postag.POSDictionaryWriter
opennlp.tools.util.TreeHeap not used anymore, when there is need for a heap use ListHeap instead

Deprecated Fields

Field and Description
opennlp.tools.tokenize.TokenizerME.alphaNumeric As of release 1.5.2, replaced by Factory.getAlphanumeric(String)

Deprecated Methods

Method and Description
opennlp.tools.chunker.ChunkerME.chunk(List, List)
opennlp.tools.chunker.Chunker.chunk(List, List) please use Chunker.chunk(String[], String[]) instead.
opennlp.tools.util.featuregen.FeatureGeneratorFactory.createFeatureGenerator(FeatureGeneratorResourceProvider)
opennlp.tools.namefind.TokenNameFinderModel.createFeatureGenerators() use TokenNameFinderFactory.createFeatureGenerators instead!
opennlp.tools.namefind.NameFinderEventStream.generateOutcomes(Span[], String, int) use the BioCodec implementation of the SequenceValidator instead!
opennlp.tools.chunker.ChunkerModel.getChunkerModel() use getChunkerSequenceModel instead. This method will be removed soon.
opennlp.tools.doccat.DoccatModel.getChunkerModel() Use DoccatModel.getMaxentModel() instead.
opennlp.tools.namefind.TokenNameFinderModel.getNameFinderModel() use getNameFinderSequenceModel instead. This method will be removed soon.
opennlp.tools.postag.POSTaggerME.getNumTags() use getAllPosTags instead!
opennlp.tools.postag.POSModel.getPosModel() use getPosSequenceModel instead. This method will be removed soon.
opennlp.tools.ml.TrainerFactory.getSequenceTrainer(Map, Map)
opennlp.tools.postag.POSModel.getTagDictionary() Use POSModel.getFactory() to get a POSTaggerFactory and POSTaggerFactory.getTagDictionary() to get a TagDictionary.
opennlp.tools.ml.TrainerFactory.isSequenceTraining(Map) use getTrainerType instead!
opennlp.tools.ml.model.TrainUtil.isSequenceTraining(Map) Use TrainerFactory.isSequenceTraining(Map) instead.
opennlp.tools.ml.TrainerFactory.isSupportEvent(Map) use getTrainerType instead!
opennlp.tools.ml.TrainerFactory.isSupportEventModelSequenceTraining(Map) use getTrainerType instead!
opennlp.tools.ml.TrainerFactory.isSupportSequence(Map) use getTrainerType instead!
opennlp.tools.ml.TrainerFactory.isSupportSequenceTraining(Map) use getTrainerType instead!
opennlp.tools.ml.model.TrainUtil.isValid(Map) Use TrainerFactory.isValid(Map) instead.
opennlp.tools.namefind.TokenNameFinderEvaluator.main(String[])
opennlp.tools.parser.Parse.main(String[])
opennlp.tools.tokenize.SimpleTokenizer.main(String[]) this method will be removed, use the new command line interface instead!
opennlp.tools.util.ListHeap.main(String[])
opennlp.tools.dictionary.serializer.DictionarySerializer.serialize(OutputStream, Iterator) Use DictionarySerializer.serialize(java.io.OutputStream, java.util.Iterator, boolean) instead
opennlp.tools.postag.POSTaggerME.tag(List)
opennlp.tools.postag.POSTagger.tag(List) call tag(String[]) instead
opennlp.tools.postag.POSTaggerME.tag(String)
opennlp.tools.postag.POSTagger.tag(String) call tag(String[]) instead use WhiteSpaceTokenizer.INSTANCE.tokenize to obtain the String array.
opennlp.tools.postag.POSTaggerME.topKSequences(List)
opennlp.tools.postag.POSTagger.topKSequences(List) call topKSequences(String[]) instead
opennlp.tools.chunker.ChunkerME.topKSequences(List, List)
opennlp.tools.chunker.Chunker.topKSequences(List, List) please use Chunker.topKSequences(String[], String[]) instead.
opennlp.tools.parser.chunking.Parser.train(ObjectStream, int, int) Please do not use anymore, use the ObjectStream train methods instead! This method will be removed soon.
opennlp.tools.parser.treeinsert.Parser.train(ObjectStream, int, int)
opennlp.tools.ml.model.TrainUtil.train(ObjectStream, Map, Map) Use TrainerFactory.getEventTrainer(Map, Map) to get an EventTrainer instead.
opennlp.tools.ml.model.TrainUtil.train(SequenceStream, Map, Map) Use TrainerFactory.getSequenceTrainer(Map, Map) to get an EventModelSequenceTrainer instead.
opennlp.tools.chunker.ChunkerME.train(String, ObjectStream, ChunkerContextGenerator, TrainingParameters) Use ChunkerME.train(String, ObjectStream, TrainingParameters, ChunkerFactory) instead.
opennlp.tools.doccat.DocumentCategorizerME.train(String, ObjectStream) Use DocumentCategorizerME.train(String, ObjectStream, TrainingParameters, DoccatFactory) instead.
opennlp.tools.doccat.DocumentCategorizerME.train(String, ObjectStream, TrainingParameters, FeatureGenerator...) Use DocumentCategorizerME.train(String, ObjectStream, TrainingParameters, DoccatFactory) instead.
opennlp.tools.parser.chunking.Parser.train(String, ObjectStream, HeadRules, int, int) use Parser.train(String, ObjectStream, HeadRules, TrainingParameters) instead and pass in a TrainingParameters object.
opennlp.tools.postag.POSTaggerME.train(String, ObjectStream, ModelType, POSDictionary, Dictionary, int, int) use POSTaggerME.train(String, ObjectStream, TrainingParameters, POSTaggerFactory) instead and pass in a POSTaggerFactory and a TrainingParameters.
opennlp.tools.postag.POSTaggerME.train(String, ObjectStream, TrainingParameters, POSDictionary, Dictionary) use POSTaggerME.train(String, ObjectStream, TrainingParameters, POSTaggerFactory) instead and pass in a POSTaggerFactory.
opennlp.tools.sentdetect.SentenceDetectorME.train(String, ObjectStream, boolean, Dictionary) Use SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters) and pass in af SentenceDetectorFactory.
opennlp.tools.sentdetect.SentenceDetectorME.train(String, ObjectStream, boolean, Dictionary, TrainingParameters) Use SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters) and pass in af SentenceDetectorFactory.
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream, boolean) Use TokenizerME.train(ObjectStream, TokenizerFactory, TrainingParameters) and pass in a TokenizerFactory
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream, boolean, TrainingParameters) Use TokenizerME.train(ObjectStream, TokenizerFactory, TrainingParameters) and pass in a TokenizerFactory
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream, Dictionary, boolean, TrainingParameters) Use TokenizerME.train(ObjectStream, TokenizerFactory, TrainingParameters) and pass in a TokenizerFactory
opennlp.tools.namefind.NameFinderME.train(String, String, ObjectStream, Map) use NameFinderME.train(String, String, ObjectStream, TrainingParameters, TokenNameFinderFactory) instead.
opennlp.tools.namefind.NameFinderME.train(String, String, ObjectStream, TrainingParameters, AdaptiveFeatureGenerator, Map) use NameFinderME.train(String, String, ObjectStream, TrainingParameters, TokenNameFinderFactory) instead.
opennlp.tools.namefind.NameFinderME.train(String, String, ObjectStream, TrainingParameters, byte[], Map) use NameFinderME.train(String, String, ObjectStream, TrainingParameters, TokenNameFinderFactory) instead.
opennlp.tools.util.CountedSet.write(String, int)
opennlp.tools.util.CountedSet.write(String, int, String)
opennlp.tools.util.CountedSet.write(String, int, String, String)

Deprecated Constructors

Constructor and Description
opennlp.tools.formats.ad.ADChunkSampleStream(InputStream, String)
opennlp.tools.formats.ad.ADNameSampleStream(InputStreamFactory, String, boolean)
opennlp.tools.formats.ad.ADNameSampleStream(InputStream, String, boolean)
opennlp.tools.formats.ad.ADPOSSampleStream(InputStream, String, boolean, boolean)
opennlp.tools.formats.ad.ADSentenceSampleStream(FileInputStream, String, boolean)
opennlp.tools.formats.BioNLP2004NameSampleStream(InputStream, int)
opennlp.tools.chunker.ChunkerCrossValidator(String, TrainingParameters, ChunkerEvaluationMonitor...) Use ChunkerCrossValidator.ChunkerCrossValidator(String, TrainingParameters, ChunkerFactory, ChunkerEvaluationMonitor...) instead.
opennlp.tools.chunker.ChunkerEventStream(ObjectStream) Use ChunkerEventStream.ChunkerEventStream(ObjectStream, ChunkerContextGenerator) instead.
opennlp.tools.chunker.ChunkerME(ChunkerModel, int) beam size is now stored inside the model
opennlp.tools.chunker.ChunkerME(ChunkerModel, int, SequenceValidator) Use ChunkerME.ChunkerME(ChunkerModel, int) instead and use the ChunkerFactory to configure the SequenceValidator.
opennlp.tools.chunker.ChunkerME(ChunkerModel, int, SequenceValidator, ChunkerContextGenerator) Use ChunkerME.ChunkerME(ChunkerModel, int) instead and use the ChunkerFactory to configure the SequenceValidator and ChunkerContextGenerator.
opennlp.tools.chunker.ChunkerModel(String, MaxentModel) Use instead.
opennlp.tools.chunker.ChunkerModel(String, MaxentModel, Map) Use ChunkerModel.ChunkerModel(String, MaxentModel, Map, ChunkerFactory) instead.
opennlp.tools.formats.Conll02NameSampleStream(Conll02NameSampleStream.LANGUAGE, InputStream, int)
opennlp.tools.formats.Conll03NameSampleStream(Conll03NameSampleStream.LANGUAGE, InputStream, int)
opennlp.tools.namefind.DefaultNameContextGenerator() use the other constructor and always provide the feature generators
opennlp.tools.dictionary.Dictionary(InputStream, boolean) This constructor is deprecated. Passing the case sensitivity flag has no effect. Use Dictionary.Dictionary(InputStream) instead and set the case sensitivity during the dictionary creation.
opennlp.tools.doccat.DoccatModel(String, MaxentModel) Use DoccatModel.DoccatModel(String, MaxentModel, Map, DoccatFactory) instead and pass in a DoccatFactory
opennlp.tools.doccat.DocumentCategorizerME(DoccatModel, FeatureGenerator...) train a DoccatModel with a specific DoccatFactory to customize the FeatureGenerators
opennlp.tools.formats.EvalitaNameSampleStream(EvalitaNameSampleStream.LANGUAGE, InputStream, int)
opennlp.tools.parser.lang.en.HeadRules(String)
opennlp.tools.namefind.NameFinderME(TokenNameFinderModel, AdaptiveFeatureGenerator, int) the beam size is now configured during training time in the trainer parameter file via beamSearch.beamSize
opennlp.tools.namefind.NameFinderME(TokenNameFinderModel, AdaptiveFeatureGenerator, int, SequenceValidator) the beam size is now configured during training time in the trainer parameter file via beamSearch.beamSize
opennlp.tools.namefind.NameFinderME(TokenNameFinderModel, int) the beam size is now configured during training time in the trainer parameter file via beamSearch.beamSize
opennlp.tools.ml.perceptron.PerceptronModel(Context[], String[], Map, String[]) use the constructor with the IndexHashTable instead!
opennlp.tools.util.PlainTextByLineStream(FileChannel, Charset) Use PlainTextByLineStream.PlainTextByLineStream(InputStreamFactory, Charset) instead.
opennlp.tools.util.PlainTextByLineStream(FileChannel, String) Use PlainTextByLineStream.PlainTextByLineStream(InputStreamFactory, String) instead.
opennlp.tools.util.PlainTextByLineStream(InputStream, Charset) Use PlainTextByLineStream.PlainTextByLineStream(InputStreamFactory, Charset) instead.
opennlp.tools.util.PlainTextByLineStream(InputStream, String) Use PlainTextByLineStream.PlainTextByLineStream(InputStreamFactory, String) instead.
opennlp.tools.util.PlainTextByLineStream(Reader) Use PlainTextByLineStream.PlainTextByLineStream(InputStreamFactory, Charset) instead.
opennlp.tools.postag.POSDictionary(BufferedReader, boolean) Use POSDictionary.create(InputStream) instead, old format might removed.
opennlp.tools.postag.POSDictionary(String) Use POSDictionary.create(InputStream) instead, old format might removed.
opennlp.tools.postag.POSDictionary(String, boolean) Use POSDictionary.create(InputStream) instead, old format might removed.
opennlp.tools.postag.POSDictionary(String, String, boolean) Use POSDictionary.create(InputStream) instead, old format might removed.
opennlp.tools.postag.POSModel(String, MaxentModel, POSDictionary, Dictionary) Use POSModel.POSModel(String, MaxentModel, Map, POSTaggerFactory) instead.
opennlp.tools.postag.POSModel(String, MaxentModel, POSDictionary, Dictionary, Map) Use POSModel.POSModel(String, MaxentModel, Map, POSTaggerFactory) instead.
opennlp.tools.postag.POSTaggerCrossValidator(String, TrainingParameters, POSDictionary, Dictionary, POSTaggerEvaluationMonitor...) use POSTaggerCrossValidator.POSTaggerCrossValidator(String, TrainingParameters, POSTaggerFactory, POSTaggerEvaluationMonitor...) instead and pass in a POSTaggerFactory.
opennlp.tools.postag.POSTaggerCrossValidator(String, TrainingParameters, POSDictionary, Integer, POSTaggerEvaluationMonitor...) use POSTaggerCrossValidator.POSTaggerCrossValidator(String, TrainingParameters, POSTaggerFactory, POSTaggerEvaluationMonitor...) instead and pass in the name of POSTaggerFactory sub-class.
opennlp.tools.postag.POSTaggerCrossValidator(String, TrainingParameters, POSDictionary, POSTaggerEvaluationMonitor...) use POSTaggerCrossValidator.POSTaggerCrossValidator(String, TrainingParameters, POSTaggerFactory, POSTaggerEvaluationMonitor...) instead and pass in a POSTaggerFactory.
opennlp.tools.postag.POSTaggerME(POSModel, int, int) the beam size should be specified in the params during training
opennlp.tools.namefind.RegexNameFinder(Pattern[])
opennlp.tools.sentdetect.SDCrossValidator(String) use SDCrossValidator.SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...) instead and pass in a TrainingParameters object.
opennlp.tools.sentdetect.SDCrossValidator(String, TrainingParameters) Use SDCrossValidator.SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...) and pass in a SentenceDetectorFactory.
opennlp.tools.sentdetect.SDCrossValidator(String, TrainingParameters, SentenceDetectorEvaluationMonitor...) use SDCrossValidator.SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...) instead and pass in a TrainingParameters object.
opennlp.tools.sentdetect.SentenceDetectorME(SentenceModel, Factory) Use a SentenceDetectorFactory to extend SentenceDetector functionality.
opennlp.tools.sentdetect.SentenceModel(String, MaxentModel, boolean, Dictionary, char[]) Use SentenceModel.SentenceModel(String, MaxentModel, Map, SentenceDetectorFactory) instead and pass in a SentenceDetectorFactory
opennlp.tools.sentdetect.SentenceModel(String, MaxentModel, boolean, Dictionary, char[], Map) Use SentenceModel.SentenceModel(String, MaxentModel, Map, SentenceDetectorFactory) instead and pass in a SentenceDetectorFactory
opennlp.tools.tokenize.SimpleTokenizer() Use INSTANCE field instead to obtain an instance, constructor will be made private in the future.
opennlp.tools.tokenize.TokenizerCrossValidator(String, boolean) use TokenizerCrossValidator.TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...) instead and pass in a TokenizerFactory
opennlp.tools.tokenize.TokenizerCrossValidator(String, boolean, TrainingParameters, TokenizerEvaluationMonitor...) use TokenizerCrossValidator.TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...) instead and pass in a TokenizerFactory
opennlp.tools.tokenize.TokenizerCrossValidator(String, Dictionary, boolean, TrainingParameters, TokenizerEvaluationMonitor...) use TokenizerCrossValidator.TokenizerCrossValidator(TrainingParameters, TokenizerFactory, TokenizerEvaluationMonitor...) instead and pass in a TokenizerFactory
opennlp.tools.tokenize.TokenizerME(TokenizerModel, Factory) use TokenizerFactory to extend the Tokenizer functionality
opennlp.tools.tokenize.TokenizerModel(String, AbstractModel, boolean) Use TokenizerModel.TokenizerModel(MaxentModel, Map, TokenizerFactory) instead and pass in a TokenizerFactory.
opennlp.tools.tokenize.TokenizerModel(String, AbstractModel, boolean, Map) Use TokenizerModel.TokenizerModel(MaxentModel, Map, TokenizerFactory) instead and pass in a TokenizerFactory.
opennlp.tools.tokenize.TokenizerModel(String, MaxentModel, Dictionary, boolean, Map) Use TokenizerModel.TokenizerModel(MaxentModel, Map, TokenizerFactory) instead and pass in a TokenizerFactory.

Deprecated Enum Constants

Enum Constant and Description
opennlp.tools.parser.ParserEventTypeEnum.CHUNK
opennlp.tools.parser.ParserEventTypeEnum.TAG