Deprecated List (Apache OpenNLP Reactor 1.5.3 API)

Deprecated Interfaces
Interface and Description

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

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.util.HashSumEventStream
opennlp.tools.postag.POSDictionaryWriter
opennlp.tools.postag.POSTaggerTrainer Use `POSTaggerME.train(String, ObjectStream, opennlp.tools.util.model.ModelType, POSDictionary, Dictionary, int, int)` instead.
opennlp.tools.lang.english.TreebankLinker will be removed soon!
opennlp.tools.lang.english.TreebankNameFinder will be removed soon!
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 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<String>, List<String>)
opennlp.tools.chunker.Chunker.chunk(List<String>, List<String>) please use `Chunker.chunk(String[], String[])` instead.
opennlp.tools.sentdetect.DefaultSDContextGenerator.collectFeatures(String, String, String, String) use `DefaultSDContextGenerator.collectFeatures(String, String, String, String, Character)` instead.
opennlp.tools.util.featuregen.FeatureGeneratorFactory.createFeatureGenerator(FeatureGeneratorResourceProvider)
opennlp.tools.postag.POSModel.getTagDictionary() Use `POSModel.getFactory()` to get a `POSTaggerFactory` and `POSTaggerFactory.getTagDictionary()` to get a `TagDictionary`.
opennlp.tools.postag.POSTaggerTrainer.main(String[])
opennlp.tools.namefind.TokenNameFinderEvaluator.main(String[])
opennlp.tools.namefind.NameFinderEventStream.main(String[])
opennlp.tools.parser.Parse.main(String[])
opennlp.tools.util.ListHeap.main(String[])
opennlp.tools.tokenize.SimpleTokenizer.main(String[])
opennlp.tools.dictionary.serializer.DictionarySerializer.serialize(OutputStream, Iterator<Entry>) Use `DictionarySerializer.serialize(java.io.OutputStream, java.util.Iterator, boolean)` instead
opennlp.tools.postag.POSTaggerME.tag(List<String>)
opennlp.tools.postag.POSTagger.tag(List<String>) 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.POSTaggerTrainer.test(AbstractModel)
opennlp.tools.postag.POSTaggerME.topKSequences(List<String>)
opennlp.tools.postag.POSTagger.topKSequences(List<String>) call `topKSequences(String[])` instead
opennlp.tools.chunker.ChunkerME.topKSequences(List<String>, List<String>)
opennlp.tools.chunker.Chunker.topKSequences(List<String>, List<String>) please use `Chunker.topKSequences(String[], String[])` instead.
opennlp.tools.doccat.DocumentCategorizerME.train(DocumentCategorizerEventStream)
opennlp.tools.namefind.NameFinderME.train(EventStream, int, int)
opennlp.tools.parser.chunking.Parser.train(EventStream, 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(EventStream, int, int)
opennlp.tools.chunker.ChunkerME.train(String, ObjectStream<ChunkSample>, ChunkerContextGenerator, TrainingParameters) Use `#train(String, ObjectStream, ChunkerContextGenerator, TrainingParameters, ChunkerFactory)` instead.
opennlp.tools.chunker.ChunkerME.train(String, ObjectStream<ChunkSample>, int, int) use `ChunkerME.train(String, ObjectStream, ChunkerContextGenerator, TrainingParameters)` instead and pass in a TrainingParameters object.
opennlp.tools.chunker.ChunkerME.train(String, ObjectStream<ChunkSample>, int, int, ChunkerContextGenerator) use `ChunkerME.train(String, ObjectStream, ChunkerContextGenerator, TrainingParameters)` instead and pass in a TrainingParameters object.
opennlp.tools.parser.chunking.Parser.train(String, ObjectStream<Parse>, HeadRules, int, int) use `Parser.train(String, ObjectStream, HeadRules, TrainingParameters)` instead and pass in a TrainingParameters object.
opennlp.tools.postag.POSTaggerME.train(String, ObjectStream<POSSample>, 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<POSSample>, TrainingParameters, POSDictionary, Dictionary) use `POSTaggerME.train(String, ObjectStream, TrainingParameters, POSTaggerFactory)` instead and pass in a `POSTaggerFactory`.
opennlp.tools.sentdetect.SentenceDetectorME.train(String, ObjectStream<SentenceSample>, boolean, Dictionary) Use `SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters)` and pass in af `SentenceDetectorFactory`.
opennlp.tools.sentdetect.SentenceDetectorME.train(String, ObjectStream<SentenceSample>, boolean, Dictionary, int, int) Use `SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters)` and pass in af `SentenceDetectorFactory`.
opennlp.tools.sentdetect.SentenceDetectorME.train(String, ObjectStream<SentenceSample>, boolean, Dictionary, TrainingParameters) Use `SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters)` and pass in af `SentenceDetectorFactory`.
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream<TokenSample>, boolean) Use `#train(String, ObjectStream, TokenizerFactory, TrainingParameters)` and pass in a `TokenizerFactory`
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream<TokenSample>, boolean, int, int) Use `#train(String, ObjectStream, TokenizerFactory, TrainingParameters)` and pass in a `TokenizerFactory`
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream<TokenSample>, boolean, TrainingParameters) Use `#train(String, ObjectStream, TokenizerFactory, TrainingParameters)` and pass in a `TokenizerFactory`
opennlp.tools.tokenize.TokenizerME.train(String, ObjectStream<TokenSample>, Dictionary, boolean, TrainingParameters) Use `#train(String, ObjectStream, TokenizerFactory, TrainingParameters)` and pass in a `TokenizerFactory`
opennlp.tools.namefind.NameFinderME.train(String, String, ObjectStream<NameSample>, byte[], Map<String, Object>, int, int) use `NameFinderME.train(String, String, ObjectStream, TrainingParameters, byte[], Map)` instead and pass in a TrainingParameters object.
opennlp.tools.namefind.NameFinderME.train(String, String, ObjectStream<NameSample>, Map<String, Object>, int, int) use `NameFinderME.train(String, String, ObjectStream, TrainingParameters, AdaptiveFeatureGenerator, Map)` instead and pass in a TrainingParameters object.
opennlp.tools.postag.POSTaggerTrainer.trainMaxentModel(EventStream, File)
opennlp.tools.postag.POSTaggerTrainer.trainMaxentModel(EventStream, int, int)
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.chunker.ChunkerCrossValidator(String, int, int) Use `ChunkerCrossValidator.ChunkerCrossValidator(String, TrainingParameters, ChunkerFactory, ChunkerEvaluationMonitor...)` instead.
opennlp.tools.chunker.ChunkerCrossValidator(String, TrainingParameters, ChunkerEvaluationMonitor...) Use `ChunkerCrossValidator.ChunkerCrossValidator(String, TrainingParameters, ChunkerFactory, ChunkerEvaluationMonitor...)` instead.
opennlp.tools.chunker.ChunkerEventStream(ObjectStream<ChunkSample>) Use `ChunkerEventStream.ChunkerEventStream(ObjectStream, ChunkerContextGenerator)` instead.
opennlp.tools.chunker.ChunkerME(ChunkerModel, int, SequenceValidator<String>) Use `ChunkerME.ChunkerME(ChunkerModel, int)` instead and use the `ChunkerFactory` to configure the `SequenceValidator`.
opennlp.tools.chunker.ChunkerME(ChunkerModel, int, SequenceValidator<String>, ChunkerContextGenerator) Use `ChunkerME.ChunkerME(ChunkerModel, int)` instead and use the `ChunkerFactory` to configure the `SequenceValidator` and `ChunkerContextGenerator`.
opennlp.tools.chunker.ChunkerME(MaxentModel)
opennlp.tools.chunker.ChunkerME(MaxentModel, ChunkerContextGenerator)
opennlp.tools.chunker.ChunkerME(MaxentModel, ChunkerContextGenerator, int)
opennlp.tools.chunker.ChunkerModel(String, AbstractModel) Use `instead.`
opennlp.tools.chunker.ChunkerModel(String, AbstractModel, Map<String, String>) Use `ChunkerModel.ChunkerModel(String, AbstractModel, Map, ChunkerFactory)` instead.
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.DocumentCategorizerME(MaxentModel) Use `DocumentCategorizerME.DocumentCategorizerME(DoccatModel)` instead.
opennlp.tools.doccat.DocumentCategorizerME(MaxentModel, FeatureGenerator...) Use `DocumentCategorizerME.DocumentCategorizerME(DoccatModel, FeatureGenerator...)` instead.
opennlp.tools.parser.lang.en.HeadRules(String)
opennlp.tools.namefind.NameFinderME(MaxentModel) Use the new model API!
opennlp.tools.namefind.NameFinderME(MaxentModel, NameContextGenerator)
opennlp.tools.namefind.NameFinderME(MaxentModel, NameContextGenerator, int)
opennlp.tools.parser.treeinsert.Parser(AbstractModel, AbstractModel, AbstractModel, POSTagger, Chunker, HeadRules)
opennlp.tools.parser.treeinsert.Parser(AbstractModel, AbstractModel, AbstractModel, POSTagger, Chunker, HeadRules, int, double)
opennlp.tools.parser.chunking.Parser(MaxentModel, MaxentModel, POSTagger, Chunker, HeadRules)
opennlp.tools.parser.chunking.Parser(MaxentModel, MaxentModel, POSTagger, Chunker, HeadRules, int, double)
opennlp.perceptron.PerceptronModel(Context[], String[], Map<String, Integer>, String[]) use the constructor with the `IndexHashTable` 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, AbstractModel, POSDictionary, Dictionary) Use `POSModel.POSModel(String, AbstractModel, Map, POSTaggerFactory)` instead.
opennlp.tools.postag.POSModel(String, AbstractModel, POSDictionary, Dictionary, Map<String, String>) Use `POSModel.POSModel(String, AbstractModel, Map, POSTaggerFactory)` instead.
opennlp.tools.postag.POSTaggerCrossValidator(String, ModelType, POSDictionary, Dictionary) use `POSTaggerCrossValidator.POSTaggerCrossValidator(String, TrainingParameters, POSTaggerFactory, POSTaggerEvaluationMonitor...)` instead and pass in a `TrainingParameters` object and a `POSTaggerFactory`.
opennlp.tools.postag.POSTaggerCrossValidator(String, ModelType, POSDictionary, Dictionary, int, int) use `POSTaggerCrossValidator.POSTaggerCrossValidator(String, TrainingParameters, POSTaggerFactory, POSTaggerEvaluationMonitor...)` instead and pass in a `TrainingParameters` object and a `POSTaggerFactory`.
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(String, TrainingParameters, POSDictionary, Integer, String, 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(AbstractModel, Dictionary)
opennlp.tools.postag.POSTaggerME(AbstractModel, Dictionary, TagDictionary)
opennlp.tools.postag.POSTaggerME(AbstractModel, POSContextGenerator)
opennlp.tools.postag.POSTaggerME(AbstractModel, POSContextGenerator, TagDictionary)
opennlp.tools.postag.POSTaggerME(AbstractModel, TagDictionary)
opennlp.tools.postag.POSTaggerME(int, AbstractModel, POSContextGenerator, TagDictionary)
opennlp.tools.postag.POSTaggerME(POSModel, int, int, SequenceValidator<String>) use `POSTaggerME.POSTaggerME(POSModel, int, int)` instead. The model knows which `SequenceValidator` to use.
opennlp.tools.sentdetect.SDCrossValidator(String) use `#SDCrossValidator(String, TrainingParameters, Dictionary, SentenceDetectorEvaluationMonitor...)` instead and pass in a TrainingParameters object.
opennlp.tools.sentdetect.SDCrossValidator(String, int, int) Use `SDCrossValidator.SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...)` and pass in a `SentenceDetectorFactory`.
opennlp.tools.sentdetect.SDCrossValidator(String, int, int, Dictionary) use `#SDCrossValidator(String, TrainingParameters, Dictionary, 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(String, TrainingParameters, Dictionary, 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, AbstractModel, boolean, Dictionary, char[]) Use `SentenceModel.SentenceModel(String, AbstractModel, Map, SentenceDetectorFactory)` instead and pass in a `SentenceDetectorFactory`
opennlp.tools.sentdetect.SentenceModel(String, AbstractModel, boolean, Dictionary, char[], Map<String, String>) Use `SentenceModel.SentenceModel(String, AbstractModel, 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, int, int) 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(String, AbstractModel, Map, TokenizerFactory)` instead and pass in a `TokenizerFactory`.
opennlp.tools.tokenize.TokenizerModel(String, AbstractModel, boolean, Map<String, String>) Use `TokenizerModel#TokenizerModel(String, AbstractModel, Map, TokenizerFactory)` instead and pass in a `TokenizerFactory`.
opennlp.tools.tokenize.TokenizerModel(String, AbstractModel, Dictionary, boolean, Map<String, String>) Use `TokenizerModel#TokenizerModel(String, AbstractModel, Map, TokenizerFactory)` instead and pass in a `TokenizerFactory`.
opennlp.tools.namefind.TokenNameFinderCrossValidator(String, int, int) use `TokenNameFinderCrossValidator.TokenNameFinderCrossValidator(String, String, TrainingParameters, byte[], Map, TokenNameFinderEvaluationMonitor...)` instead and pass in a TrainingParameters object.
opennlp.tools.namefind.TokenNameFinderCrossValidator(String, String, byte[], Map<String, Object>, int, int) use `TokenNameFinderCrossValidator.TokenNameFinderCrossValidator(String, String, TrainingParameters, byte[], Map, TokenNameFinderEvaluationMonitor...)` instead and pass in a TrainingParameters object.
opennlp.tools.namefind.TokenNameFinderCrossValidator(String, String, int, int) use `TokenNameFinderCrossValidator.TokenNameFinderCrossValidator(String, String, TrainingParameters, byte[], Map, TokenNameFinderEvaluationMonitor...)` instead and pass in a TrainingParameters object.

Deprecated Enum Constants
Enum Constant and Description

opennlp.tools.parser.ParserEventTypeEnum.CHUNK

opennlp.tools.parser.ParserEventTypeEnum.TAG

Deprecated API

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