# All Classes and Interfaces

Class
Description
AbstractBottomUpParser
Abstract class which contains code to tag and chunk parses for bottom up parsing and leaves implementation of advancing parses and completing parses to extend class.
AbstractContextGenerator
Abstract class containing many of the methods used to generate contexts for parsing.
AbstractDataIndexer
Abstract `DataIndexer` implementation for collecting event and context counts used in training.
AbstractEventModelSequenceTrainer
A basic `EventModelSequenceTrainer` implementation that processes `events`.
AbstractEventStream<T>
A base `ObjectStream` implementation for events.
AbstractEventTrainer
A basic `EventTrainer` implementation.
AbstractMLModelWriter
AbstractModel
A basic `MaxentModel` implementation.
AbstractModel.ModelType
AbstractModelReader
An abstract, basic implementation of a model reader.
AbstractModelWriter
An abstract, basic implementation of a model writer.
AbstractObjectStream<T>
A base `ObjectStream` implementation.
AbstractParserEventStream
Abstract class extended by parser event streams which perform tagging and chunking.
AbstractSampleStreamFactory<T,P>
Base class for sample stream factories.
AbstractToSentenceSampleStream<T>
AbstractTrainer
AdaptiveFeatureGenerator
An interface for generating features for name entity identification and for updating document level contexts.
ADChunkSampleStream
Parser for Floresta Sita(c)tica Arvores Deitadas corpus, output to for the Portuguese Chunker training.
ADChunkSampleStreamFactory
A Factory to create a Arvores Deitadas ChunkStream from the command line utility.
ADChunkSampleStreamFactory.Parameters
AdditionalContextFeatureGenerator
The `AdditionalContextFeatureGenerator` generates the context from the passed in additional context.
ADNameSampleStream
Parser for Floresta Sita(c)tica Arvores Deitadas corpus, output to for the Portuguese NER training.
ADNameSampleStreamFactory
A Factory to create a Arvores Deitadas NameSampleDataStream from the command line utility.
ADNameSampleStreamFactory.Parameters
ADPOSSampleStream
Note: Do not use this class, internal use only!
ADPOSSampleStreamFactory
Note: Do not use this class, internal use only!
ADPOSSampleStreamFactory.Parameters
ADSentenceSampleStream
Note: Do not use this class, internal use only!
ADSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
ADSentenceSampleStreamFactory.Parameters
ADSentenceStream
Stream filter which merges text lines into sentences, following the Arvores Deitadas syntax.
ADSentenceStream.Sentence
ADSentenceStream.SentenceParser
Parses a sample of AD corpus.
ADSentenceStream.SentenceParser.Leaf
Represents the AD leaf
ADSentenceStream.SentenceParser.Node
Represents the AD node
ADSentenceStream.SentenceParser.TreeElement
Represents a tree element, Node or Leaf
ADTokenSampleStreamFactory
Note: Do not use this class, internal use only!
ADTokenSampleStreamFactory.Parameters
AggregateCharSequenceNormalizer
A `CharSequenceNormalizer` implementation that aggregates the functionality of other normalizers.
AggregatedFeatureGenerator
The `AggregatedFeatureGenerator` aggregates a set of `feature generators` and calls them to generate the features.
AggregatedFeatureGeneratorFactory
A `GeneratorFactory` that produces `AggregatedFeatureGenerator` instances when `AggregatedFeatureGeneratorFactory.create()` is called.
Among
Internal class used by Snowball stemmers
AncoraSpanishHeadRules
Class for storing the Ancora Spanish head rules associated with parsing.
AncoraSpanishHeadRules.HeadRulesSerializer
AnnotationConfiguration
Encapsulates a type to class mapping for entities, relations, events, etc.
AnnotatorNoteAnnotation
arabicStemmer
This class implements the stemming algorithm defined by a snowball script.
ArrayMath
Utility class for simple vector arithmetic.
ArtifactProvider
Provides access to model persisted artifacts.
ArtifactSerializer<T>
Responsible to create an artifact from an `InputStream`.
AttachContextGenerator
Generates predictive contexts for deciding how constituents should be attached.
AttributeAnnotation
Attributes
The `Attributes` class stores name value pairs.
BagOfWordsFeatureGenerator
Generates a feature for each word in a document.
BaseLink
Represents a minimal tuple of information.
BaseModel
This is a common base model which can be used by the components' specific model classes.
BaseToolFactory
Base class for all tool `factories`.
BasicContextGenerator
A `ContextGenerator` implementation for maxent decisions, assuming that the input given to the `BasicContextGenerator.getContext(String)` method is a String containing contextual predicates separated by spaces, for instance:
BasicFormatParams
Common format parameters.
BasicTrainingParams
Common training parameters.
BeamSearch
Performs k-best search over a sequence.
BeamSearchContextGenerator<T>
Interface for context generators used with a sequence beam search.
BigramNameFeatureGenerator
Adds bigram features based on tokens and token classes.
BigramNameFeatureGeneratorFactory
A `GeneratorFactory` that produces `BigramNameFeatureGenerator` instances when `BigramNameFeatureGeneratorFactory.create()` is called.
BilouCodec
The default `SequenceCodec` implementation according to the `BILOU` scheme.
BilouNameFinderSequenceValidator
A `SequenceValidator` implementation for the `BilouCodec`.
BinaryFileDataReader
A `DataReader` that reads files from a binary format.
BinaryGISModelReader
A `GISModelReader` that reads models from a binary format.
BinaryGISModelWriter
A `GISModelWriter` that writes models in a binary format.
BinaryNaiveBayesModelReader
A `NaiveBayesModelReader` that reads models from a binary format.
BinaryNaiveBayesModelWriter
A `NaiveBayesModelWriter` that writes models in a binary format.
BinaryPerceptronModelReader
A `PerceptronModelReader` that reads models from a binary format.
BinaryPerceptronModelWriter
A `PerceptronModelWriter` that writes models in a binary format.
BinaryQNModelReader
A `QNModelReader` that reads models from a binary format.
BinaryQNModelWriter
A `QNModelWriter` that writes models in a binary format.
BioCodec
The default `SequenceCodec` implementation according to the `BIO` scheme: B: 'beginning' of a NE I: 'inside', the word is inside a NE O: 'outside', the word is a regular word outside a NE See also the paper by Roth D. and Ratinov L.: Design Challenges and Misconceptions in Named Entity Recognition.
BioNLP2004NameSampleStream
A `sample stream` for the training files of the BioNLP/NLPBA 2004 shared task.
BioNLP2004NameSampleStreamFactory
BioNLP2004NameSampleStreamFactory.Parameters
BratAnnotation
BratAnnotationStream
Reads the annotations from the brat `.ann` annotation file.
BratDocument
Brat (brat rapid annotation tool) is based on the stav visualiser which was originally made in order to visualise BioNLP'11 Shared Task data.
BratDocumentParser
BratDocumentStream
BratNameSampleStream
Generates Name Sample objects for a Brat Document object.
BratNameSampleStreamFactory
Note: Do not use this class, internal use only!
BratNameSampleStreamFactory.Parameters
BrownBigramFeatureGenerator
Generates Brown cluster features for token bigrams.
BrownCluster
Class to load a Brown cluster document in the format: `word\tword_class\tprob`.
BrownCluster.BrownClusterSerializer
BrownClusterBigramFeatureGeneratorFactory
A `GeneratorFactory` that produces `BrownBigramFeatureGenerator` instances when `BrownClusterBigramFeatureGeneratorFactory.create()` is called.
BrownClusterTokenClassFeatureGeneratorFactory
A `GeneratorFactory` that produces `BrownTokenClassFeatureGenerator` instances when `BrownClusterTokenClassFeatureGeneratorFactory.create()` is called.
BrownClusterTokenFeatureGeneratorFactory
A `GeneratorFactory` that produces `BrownTokenFeatureGenerator` instances when `BrownClusterTokenFeatureGeneratorFactory.create()` is called.
BrownTokenClasses
Obtain the paths listed in the pathLengths array from the Brown class.
BrownTokenClassFeatureGenerator
Generates `BrownCluster` features for current token and token class.
BrownTokenFeatureGenerator
Generates `BrownCluster` features for current token.
BuildContextGenerator
Generates predictive contexts for deciding how constituents should be combined.
BuildContextGenerator
Creates the features or contexts for the building phase of parsing.
BuildModelUpdaterTool
ByteArraySerializer
An `ArtifactSerializer` implementation for binary data, kept in `byte[]`.
Cache<K,V>
Provides fixed size, pre-allocated, least recently used replacement cache.
CachedFeatureGenerator
Caches features of the aggregated `generators`.
CachedFeatureGeneratorFactory
A `GeneratorFactory` that produces `CachedFeatureGenerator` instances when `CachedFeatureGeneratorFactory.create()` is called.
catalanStemmer
This class implements the stemming algorithm defined by a snowball script.
CensusDictionaryCreatorTool
This tool helps create a loadable dictionary for the `NameFinder`, from data collected from US Census data.
CharacterNgramFeatureGenerator
The `CharacterNgramFeatureGenerator` uses character ngrams to generate features about each token.
CharacterNgramFeatureGeneratorFactory
A `GeneratorFactory` that produces `CharacterNgramFeatureGenerator` instances when `CharacterNgramFeatureGeneratorFactory.create()` is called.
CharSequenceNormalizer
A char sequence normalizer, used to adjusting (prune, substitute, add, etc.)
CheckContextGenerator
Generates predictive context for deciding when a constituent is complete.
CheckContextGenerator
Generates predictive context for deciding when a constituent is complete.
CheckModelUpdaterTool
Trains a new check model.
ChecksumEventStream
A `Checksum`-based `event stream` implementation.
CHMStringDeduplicator
A `StringInterner` implementation by Aleksey Shipilëv with relaxed canonical requirements.
CHMStringInterner
A `StringInterner` implementation based on `ConcurrentHashMap` by Aleksey Shipilëv.
ChunkContextGenerator
Creates predictive context for the pre-chunking phases of parsing.
Chunker
The interface for chunkers which provide chunk tags for a sequence of tokens.
ChunkerContextGenerator
Interface for a `BeamSearchContextGenerator` used in syntactic chunking.
ChunkerConverterTool
Tool to convert multiple data formats into native OpenNLP chunker training format.
ChunkerCrossValidator
Cross validator for `Chunker`.
ChunkerCrossValidatorTool
ChunkerDetailedFMeasureListener
ChunkerEvaluationMonitor
A marker interface for evaluating `chunkers`.
ChunkerEvaluator
The `ChunkerEvaluator` measures the performance of the given `Chunker` with the provided reference `samples`.
ChunkerEvaluatorTool
A default `ChunkSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
ChunkerEventStream
Class for creating an event stream out of data files for training a `Chunker`.
ChunkerFactory
ChunkerME
The class represents a maximum-entropy-based `Chunker`.
ChunkerMETool
ChunkerModel
The `ChunkerModel` is the model used by a learnable `Chunker`.
ChunkerModelLoader
Loads a `ChunkerModel` for the command line tools.
ChunkerModelSerializer
An `ArtifactSerializer` implementation for `models`.
ChunkerSampleStreamFactory
Factory producing OpenNLP `ChunkSampleStream`s.
ChunkerSampleStreamFactory.Parameters
ChunkerTrainerTool
ChunkEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
ChunkSample
Class for holding chunks for a single unit of text.
ChunkSampleSequenceStream
A `SequenceStream` implementation encapsulating `samples`.
ChunkSampleStream
Parses the conll 2000 shared task shallow parser training data.
ChunkSampleStream
CollectionObjectStream<E>
An `ObjectStream` implementation that works on a `Collection` of `CollectionObjectStream` as source for elements.
ComparableEvent
A maxent event representation which we can use to sort based on the predicates indexes contained in the events.
ComparablePredicate
A maxent predicate representation which we can use to sort based on the outcomes.
ConfigurablePOSContextGenerator
A configurable `context generator` for a `POSTagger`.
Conll02NameSampleStream
Parser for the Dutch and Spanish ner training files of the CONLL 2002 shared task.
Conll02NameSampleStream.LANGUAGE
Conll02NameSampleStreamFactory
Note: Do not use this class, internal use only!
Conll02NameSampleStreamFactory.Parameters
Conll03NameSampleStream
An import stream which can parse the CONLL03 data.
Conll03NameSampleStream.LANGUAGE
Conll03NameSampleStreamFactory
Conll03NameSampleStreamFactory.Parameters
ConlluLemmaSampleStream
ConlluLemmaSampleStreamFactory
Note: Do not use this class, internal use only!
ConlluLemmaSampleStreamFactory.Parameters
ConlluPOSSampleStream
ConlluPOSSampleStreamFactory
Note: Do not use this class, internal use only!
ConlluPOSSampleStreamFactory.Parameters
ConlluSentence
ConlluSentenceSampleStream
ConlluSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
ConlluSentenceSampleStreamFactory.Parameters
ConlluStream
The CoNNL-U Format is specified here.
ConlluTagset
ConlluTokenSampleStream
ConlluTokenSampleStreamFactory
Note: Do not use this class, internal use only!
ConlluTokenSampleStreamFactory.Parameters
ConlluWordLine
ConllXPOSSampleStream
Parses the data from the CONLL 06 shared task into POS Samples.
ConllXPOSSampleStreamFactory
Note: Do not use this class, internal use only!
ConllXPOSSampleStreamFactory.Parameters
ConllXSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
ConllXSentenceSampleStreamFactory.Parameters
ConllXTokenSampleStreamFactory
Note: Do not use this class, internal use only!
ConllXTokenSampleStreamFactory.Parameters
Cons
Holds feature information about a specific `Parse` node.
ConstitParseSampleStream
ConstitParseSampleStreamFactory
Note: Do not use this class, internal use only!
Constituent
Holds constituents when reading `parses`.
Context
Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
ContextGenerator<T>
Represents a generator of contexts for maxent decisions.
CrossValidationPartitioner<E>
Provides access to training and test partitions for n-fold cross validation.
CrossValidationPartitioner.TrainingSampleStream<E>
The `CrossValidationPartitioner.TrainingSampleStream` which iterates over all training elements.
CVParams
Common cross validator parameters.
danishStemmer
This class implements the stemming algorithm defined by a snowball script.
DataIndexer
Represents an indexer which compresses events in memory and performs feature selection.
DataIndexerFactory
A factory that produces `DataIndexer` instances.
DataReader
Describes generic ways to read data from a `DataInputStream`.
DataStream
An interface for objects which can deliver a stream of training data to be supplied to an EventStream.
DefaultChunkerContextGenerator
Features based on chunking model described in Fei Sha and Fernando Pereira.
DefaultChunkerSequenceValidator
The default chunker `SequenceValidator` implementation.
DefaultEndOfSentenceScanner
Default implementation of the `EndOfSentenceScanner`.
DefaultLanguageDetectorContextGenerator
A context generator for `language detector`.
DefaultLemmatizerContextGenerator
Simple feature generator for learning statistical lemmatizers.
DefaultLemmatizerSequenceValidator
The default lemmatizer `SequenceValidator` implementation.
DefaultNameContextGenerator
A `NameContextGenerator` implementation for determining contextual features for a `tag-chunk` style named-entity recognizer.
DefaultPOSContextGenerator
A default `context generator` for a `POSTagger`.
DefaultPOSSequenceValidator
The default POS tagger `SequenceValidator` implementation.
DefaultSDContextGenerator
Generate event contexts for maxent decisions for sentence detection.
DefaultTokenContextGenerator
A default `TokenContextGenerator` which produces events for maxent decisions for tokenization.
DefaultTrainingProgressMonitor
The default implementation of `TrainingProgressMonitor`.
DefinitionFeatureGeneratorFactory
A `GeneratorFactory` that produces `OutcomePriorFeatureGenerator` instances when `DefinitionFeatureGeneratorFactory.create()` is called.
DetokenEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
DetokenizationDictionary
DetokenizationDictionary.Operation
Detokenizer
A `Detokenizer` merges tokens back to their detokenized representation.
Detokenizer.DetokenizationOperation
This enum contains an operation for every token to merge the tokens together to their detokenized form.
DetokenizerEvaluator
The `DetokenizerEvaluator` measures the performance of the given `Detokenizer` with the provided reference `samples`.
DetokenizerParameter
DetokenizerSampleStreamFactory<T,P>
Base class for factories which need a `Detokenizer`.
DetokenizeSentenceSampleStream
Dictionary
An iterable and serializable dictionary implementation.
DictionaryBuilderTool
DictionaryDetokenizer
A rule based detokenizer.
DictionaryDetokenizerTool
DictionaryEntryPersistor
A persistor used by for reading and writing `dictionaries` of all kinds.
DictionaryFeatureGenerator
The `DictionaryFeatureGenerator` uses a `DictionaryNameFinder` to generate features for detected names based on the `InSpanGenerator`.
DictionaryFeatureGeneratorFactory
A `GeneratorFactory` that produces `DictionaryFeatureGenerator` instances when `DictionaryFeatureGeneratorFactory.create()` is called.
DictionaryLemmatizer
A `Lemmatizer` implementation that works by simple dictionary lookup into a `Map` built from a file containing, for each line:
DictionaryNameFinder
This is a `Dictionary` based `name finder`.
DictionarySerializer
An `ArtifactSerializer` implementation for `dictionaries`.
DirectorySampleStream
The directory sample stream allows for creating an `ObjectStream<File>` from a directory listing of files.
DoccatConverterTool
Tool to convert multiple data formats into native OpenNLP doccat training format.
DoccatCrossValidator
Cross validator for `DocumentCategorizer`.
DoccatCrossValidatorTool
DoccatEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
DoccatEvaluationMonitor
A marker interface for evaluating `doccat`.
DoccatEvaluatorTool
A default `DocumentSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
DoccatFactory
The factory that provides Doccat default implementations and resources.
DoccatFineGrainedReportListener
Generates a detailed report for the POS Tagger.
DoccatModel
A model for document categorization
DoccatModelLoader
Loads a `DoccatModel` for the command line tools.
DoccatTool
DoccatTrainerTool
DocumentBeginFeatureGenerator
This feature generator creates document begin features.
DocumentBeginFeatureGeneratorFactory
A `GeneratorFactory` that produces `DocumentBeginFeatureGenerator` instances when `DocumentBeginFeatureGeneratorFactory.create()` is called.
DocumentCategorizer
Interface for classes which categorize documents.
DocumentCategorizerEvaluator
The `DocumentCategorizerEvaluator` measures the performance of the given `DocumentCategorizer` with the provided reference `samples`.
DocumentCategorizerEventStream
Iterator-like class for modeling document classification events.
DocumentCategorizerME
A Max-Ent based implementation of `DocumentCategorizer`.
DocumentNameFinder
Interface for processing an entire document allowing a `TokenNameFinder` to use context from the entire document.
DocumentSample
Class which holds a classified document and its category.
DocumentSampleStream
Reads in string encoded training samples, parses them and outputs `DocumentSample` objects.
DocumentSampleStreamFactory
Factory producing OpenNLP `DocumentSampleStream`s.
DocumentSampleStreamFactory.Parameters
DocumentToLineStream
Reads a plain text file and return each line as a `String` object.
DownloadUtil
This class facilitates the downloading of pretrained OpenNLP models.
dutchStemmer
This class implements the stemming algorithm defined by a snowball script.
DynamicEvalParameters
EmojiCharSequenceNormalizer
A `EmojiCharSequenceNormalizer` implementation that normalizes text in terms of emojis.
EmptyLinePreprocessorStream
`ObjectStream` to clean up empty lines for empty line separated document streams.
- Skips empty line at training data start
- Transforms multiple empty lines in a row into one
- Replaces white space lines with empty lines
- TODO: Terminates last document with empty line if it is missing
This stream should be used by the components that mark empty lines to mark document boundaries.
EncodingParameter
Encoding parameter.
EndOfSentenceScanner
Scans `CharSequence`, `StringBuffer`, and `char[]` for the offsets of sentence ending characters.
englishStemmer
This class implements the stemming algorithm defined by a snowball script.
EntityLinker<T>
EntityLinkers establish connections with external data to enrich extracted entities.
EntityLinkerFactory
Generates a `EntityLinker` instances via a `properties` file configuration.
EntityLinkerProperties
Properties wrapper for `EntityLinker` implementations.
EntityLinkerTool
Entry
An `Entry` is a `StringList` which can optionally be mapped to attributes.
EntryInserter
EvalitaNameSampleStream
Parser for the Italian NER training files of the Evalita 2007 and 2009 NER shared tasks.
EvalitaNameSampleStream.LANGUAGE
EvalitaNameSampleStreamFactory
Note: Do not use this class, internal use only!
EvalitaNameSampleStreamFactory.Parameters
EvalParameters
This class encapsulates the variables used in producing probabilities from a model and facilitates passing these variables to the eval method.
EvaluationMonitor<T>
Evaluator<T>
An abstract base class for evaluators.
EvaluatorParams
Common evaluation parameters.
Event
The context of a decision point during training.
EventAnnotation
EventModelSequenceTrainer<T>
A specialized `Trainer` that is based on a 'EventModelSequence' approach.
EventTraceStream
EventTrainer
A specialized `Trainer` that is based on an `Event` approach.
Experimental
Indicates that a certain API feature is not stable and might change with a new release.
ExtensionLoader
The `ExtensionLoader` is responsible to load extensions to the OpenNLP library.
ExtensionNotLoadedException
Exception indicates that an OpenNLP extension could not be loaded.
ExtensionServiceKeys
Factory
Factory
FeatureGenerator
Interface for generating features for document categorization.
FeatureGeneratorResourceProvider
The `FeatureGeneratorResourceProvider` provides access to the resources available in the model.
FeatureGeneratorUtil
This class provide common utilities for feature generation.
FileEventStream
Class for using a file of `events` as an `event stream`.
FileToByteArraySampleStream
Note: Do not use this class, internal use only!
FileToStringSampleStream
Provides the ability to read the contents of files contained in an object stream of files.
FilterObjectStream<S,T>
Abstract base class for filtering `streams`.
FineGrainedEvaluatorParams
Common evaluation parameters.
finnishStemmer
This class implements the stemming algorithm defined by a snowball script.
FMeasure
The `FMeasure` is a utility class for `evaluators` which measures precision, recall and the resulting f-measure.
frenchStemmer
This class implements the stemming algorithm defined by a snowball script.
Function
Interface for a function.
GapLabeler
Represents a labeler for nodes which contain traces so that these traces can be predicted by a `Parser`.
GeneratorFactory
Creates a set of feature generators based on a provided XML descriptor.
GeneratorFactory.AbstractXmlFeatureGeneratorFactory
GenericModelReader
An generic `AbstractModelReader` implementation.
GenericModelSerializer
An `ArtifactSerializer` implementation for `models`.
GenericModelWriter
An generic `AbstractModelWriter` implementation.
germanStemmer
This class implements the stemming algorithm defined by a snowball script.
GISModel
A maximum entropy model which has been trained using the Generalized Iterative Scaling (GIS) procedure.
GISModelReader
The base class for readers of `GIS models`.
GISModelWriter
The base class for writers of `GIS models`.
GISTrainer
An implementation of Generalized Iterative Scaling (GIS).
Glove
GloVe is an unsupervised learning algorithm for obtaining vector representations for words.
greekStemmer
This class implements the stemming algorithm defined by a snowball script.
HeadRules
Encoder for head rules associated with parsing.
HeadRules
Class for storing the English `HeadRules` associated with parsing.
HeadRules.HeadRulesSerializer
HMStringInterner
A `StringInterner` implementation based on `HashMap` by Aleksey Shipilëv.
hungarianStemmer
This class implements the stemming algorithm defined by a snowball script.
Index
This classes indexes `string lists`.
indonesianStemmer
This class implements the stemming algorithm defined by a snowball script.
InputStreamFactory
Allows repeated reads through a stream for certain model building types.
InSpanGenerator
Generates features if the tokens are recognized by the provided `TokenNameFinder`.
InsufficientTrainingDataException
This exception indicates that the provided training data is insufficient to train a desired model.
Internal
Classes, fields, or methods annotated `&#64;Internal` are for OpenNLP internal use only.
InvalidFormatException
This exception indicates that a resource violates the expected data format.
IrishSentenceBankDocument
A structure to hold an Irish Sentence Bank document, which is a collection of tokenized sentences.
IrishSentenceBankDocument.IrishSentenceBankFlex
IrishSentenceBankDocument.IrishSentenceBankSentence
IrishSentenceBankSentenceStreamFactory
Note: Do not use this class, internal use only!
IrishSentenceBankSentenceStreamFactory.Parameters
IrishSentenceBankTokenSampleStreamFactory
Note: Do not use this class, internal use only!
IrishSentenceBankTokenSampleStreamFactory.Parameters
irishStemmer
This class implements the stemming algorithm defined by a snowball script.
italianStemmer
This class implements the stemming algorithm defined by a snowball script.
IterDeltaAccuracyUnderTolerance
A `StopCriteria` implementation to identify whether the absolute difference between the training accuracy of current and previous iteration is under the defined tolerance.
JvmStringInterner
A `StringInterner` implementation based on `String.intern()`.
Language
Class for holding the document language and its confidence
LanguageDetector
The interface for `LanguageDetector` which predicts the `Language` for a context.
LanguageDetectorConfig
LanguageDetectorContextGenerator
A context generator interface for `LanguageDetector`.
LanguageDetectorConverterTool
Tool to convert multiple data formats into native OpenNLP language detection training format.
LanguageDetectorCrossValidator
Cross validator for `LanguageDetector`.
LanguageDetectorCrossValidatorTool
LanguageDetectorEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
LanguageDetectorEvaluationMonitor
A marker interface for evaluating `language detectors`.
LanguageDetectorEvaluator
The `LanguageDetectorEvaluator` measures the performance of the given `LanguageDetector` with the provided reference `LanguageSample`s.
LanguageDetectorEvaluatorTool
A default `LanguageSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
LanguageDetectorEventStream
Iterator-like class for modeling an event stream of `samples`.
LanguageDetectorFactory
Default factory used by `LanguageDetector`.
LanguageDetectorFineGrainedReportListener
Generates a detailed report for the POS Tagger.
LanguageDetectorME
Implements a learnable `LanguageDetector`.
LanguageDetectorModel
The `LanguageDetectorModel` is the model used by a learnable `LanguageDetector`.
LanguageDetectorModelLoader
Loads a `LanguageDetectorModel` for the command line tools.
LanguageDetectorSampleStream
This class reads in string encoded `training samples`, parses them and outputs `LanguageSample` objects.
LanguageDetectorSampleStreamFactory
Factory producing OpenNLP `lang detector sample streams`.
LanguageDetectorSampleStreamFactory.Parameters
LanguageDetectorTool
LanguageDetectorTrainerTool
LanguageModel
A language model can calculate the probability p (between 0 and 1) of a certain `sequence of tokens`, given its underlying vocabulary.
LanguageParams
LanguageSample
Holds a classified document and its `Language`.
LanguageSampleStreamFactory<T,P>
Stream factory for those streams which carry language.
LeipzigLanguageSampleStream
LeipzigLanguageSampleStreamFactory
Note: Do not use this class, internal use only!
LeipzigLanguageSampleStreamFactory.Parameters
LemmaEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
LemmaSample
Represents a lemmatized sentence.
LemmaSampleEventStream
Class for creating an event stream out of data files for training a probabilistic `Lemmatizer`.
LemmaSampleSequenceStream
A `SequenceStream` implementation encapsulating `samples`.
LemmaSampleStream
Reads data for training and testing the `Lemmatizer`.
Lemmatizer
The common interface for lemmatizers.
LemmatizerContextGenerator
Interface for the context generator used for probabilistic `Lemmatizer`.
LemmatizerEvaluationMonitor
A marker interface for evaluating `lemmatizers`.
LemmatizerEvaluator
The `LemmatizerEvaluator` measures the performance of the given `Lemmatizer` with the provided reference `samples`.
LemmatizerEvaluatorTool
A default `LemmaSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
LemmatizerFactory
The factory that provides `Lemmatizer` default implementation and resources.
LemmatizerFineGrainedReportListener
Generates a detailed report for the Lemmatizer.
LemmatizerME
A probabilistic `Lemmatizer` implementation.
LemmatizerMETool
LemmatizerModel
The `LemmatizerModel` is the model used by a learnable `Lemmatizer`.
LemmatizerModelLoader
Loads a `LemmatizerModel` for the command line tools.
LemmatizerSampleStreamFactory
Factory producing OpenNLP `LemmaSampleStream`s.
LemmatizerSampleStreamFactory.Parameters
LemmatizerTrainerTool
LetsmtDocument
A structure to hold the letsmt document.
LetsmtDocument.LetsmtDocumentHandler
A `content handler` to receive and process SAX events.
LetsmtDocument.LetsmtSentence
LetsmtSentenceStreamFactory
Note: Do not use this class, internal use only!
LetsmtSentenceStreamFactory.Parameters
LineSearch
Performs line search to find a minimum.
LineSearch.LineSearchResult
Represents a `LineSearch` result encapsulating the relevant data at a point in time during computation.
LinkedSpan<T>
A default, extended `Span` that holds additional information about a `Span`.
LogLikelihoodThresholdBreached
A `StopCriteria` implementation to identify whether the difference between the log likelihood of current and previous iteration is under the defined threshold.
LogPrintStream
This class serves as an adapter for a `Logger` used within a `PrintStream`.
LogProbabilities<T>
Class implementing the probability distribution over labels returned by a classifier as a log of probabilities.
LogProbability<T>
A class implementing the logarithmic `Probability` for a label.
MarkableFileInputStreamFactory
A factory that creates `MarkableFileInputStream` from a `File`
Masc
A simple marker interface for classes that support or refer to the `Masc.MASC_FORMAT`.
MascDocument
MascDocumentStream
MascNamedEntityParser
A class to process the MASC Named entity stand-off annotation file
MascNamedEntitySampleStream
MascNamedEntitySampleStreamFactory
Note: Do not use this class, internal use only!
MascNamedEntitySampleStreamFactory.Parameters
MascPennTagParser
A class for parsing MASC's Penn tagging/tokenization stand-off annotation
MascPOSSampleStream
MascPOSSampleStreamFactory
Note: Do not use this class, internal use only!
MascPOSSampleStreamFactory.Parameters
MascSentence
MascSentenceSampleStream
MascSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
MascSentenceSampleStreamFactory.Parameters
MascToken
A specialized `Span` to express tokens in `documents`.
MascTokenSampleStream
MascTokenSampleStreamFactory
Note: Do not use this class, internal use only!
MascTokenSampleStreamFactory.Parameters
MascWord
MaxentModel
Interface for maximum entropy models.
Mean
Calculates the arithmetic mean of values added with the `Mean.add(double)` method.
ModelParameterChunker
A helper class that handles Strings with more than 64k (65535 bytes) in length.
ModelType
A model type to pattern enumeration.
ModelType
Enumeration of supported model types.
ModelUtil
Utility class for handling of `models`.
MosesSentenceSampleStream
Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair.
MosesSentenceSampleStreamFactory
Factory producing OpenNLP `MosesSentenceSampleStream` objects.
MosesSentenceSampleStreamFactory.Parameters
Muc6NameSampleStreamFactory
Muc6NameSampleStreamFactory.Parameters
MucNameContentHandler
MucNameSampleStream
MutableContext
An extension of `Context` used to store parameters or expected values associated with this context which can be updated or assigned.
MutableInt
This is a non-thread safe mutable int.
MutableTagDictionary
Interface that allows `TagDictionary` entries to be added and removed.
NaiveBayesEvalParameters
Specialized `parameters` for the evaluation of a naive bayes classifier
NaiveBayesModel
A `MaxentModel` implementation of the multinomial Naive Bayes classifier model.
NaiveBayesModelReader
The base class for readers of `models`.
NaiveBayesModelWriter
The base class for `NaiveBayesModel` writers.
NaiveBayesTrainer
Trains `models` using the combination of EM algorithm and Naive Bayes classifier which is described in:
NameContextGenerator
Interface for generating the context for a `name finder` by specifying a set of feature generators.
NameEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
NameFinderCensus90NameStream
This class helps to read the US Census data from the files to build a StringList for each dictionary entry in the name-finder dictionary.
NameFinderEventStream
Class for creating an event stream out of data files for training an `TokenNameFinder`.
NameFinderME
A maximum-entropy-based `name finder` implementation.
NameFinderSequenceValidator
The default name finder `SequenceValidator` implementation.
NameSample
Encapsulates names for a single unit of text.
NameSampleCountersStream
Counts tokens, sentences and names by type.
NameSampleDataStream
The `NameSampleDataStream` class converts tagged tokens provided by a `DataStream` to `NameSample` objects.
NameSampleDataStreamFactory
Factory producing OpenNLP `NameSampleDataStream`s.
NameSampleDataStreamFactory.Parameters
NameSampleSequenceStream
A `SequenceStream` implementation encapsulating `samples`.
NameSampleTypeFilter
A `stream` which removes `name samples` which do not have a certain type.
NameToSentenceSampleStream
Note: Do not use this class, internal use only!
NameToSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
NameToTokenSampleStream
Note: Do not use this class, internal use only!
NameToTokenSampleStreamFactory
Note: Do not use this class, internal use only!
NameToTokenSampleStreamFactory.Parameters
NegLogLikelihood
Evaluates negative log-likelihood and its gradient from `DataIndexer`.
NewlineSentenceDetector
The Newline `SentenceDetector` assumes that sentences are line delimited and recognizes one sentence per non-empty line.
NGramCharModel
The `NGramCharModel` can be used to create character ngrams.
NGramFeatureGenerator
Generates ngram features for a document.
NGramGenerator
Generates an nGram, via an optional separator, and returns the grams as a list of strings
NGramLanguageModel
A `LanguageModel` based on a `NGramModel` using Stupid Backoff to get the probabilities of the ngrams.
NGramLanguageModelTool
Command line tool for `NGramLanguageModel`.
NGramModel
The `NGramModel` can be used to crate ngrams and character ngrams.
NGramUtils
Utility class for ngrams.
NKJPSegmentationDocument
NKJPSegmentationDocument.Pointer
NKJPSentenceSampleStream
NKJPSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
NKJPSentenceSampleStreamFactory.Parameters
NKJPTextDocument
The National corpus of Polish (NKJP) format.
NoOpStringInterner
A no-op `StringInterner` implementation, which does not intern.
norwegianStemmer
This class implements the stemming algorithm defined by a snowball script.
NumberCharSequenceNormalizer
A `NumberCharSequenceNormalizer` implementation that normalizes text in terms of numbers.
ObjectDataReader
A `DataReader` implementation based on `ObjectInputStream`.
ObjectStream<T>
Reads `objects` from a stream.
ObjectStreamUtils
OnePassDataIndexer
A `DataIndexer` for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates.
OnePassRealValueDataIndexer
A `DataIndexer` for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates and maintains event values.
OntoNotesFormatParameters
OntoNotesNameSampleStream
Name Sample Stream parser for the OntoNotes 4.0 named entity files.
OntoNotesNameSampleStreamFactory
Note: Do not use this class, internal use only!
OntoNotesParseSampleStream
OntoNotesParseSampleStreamFactory
Note: Do not use this class, internal use only!
OntoNotesPOSSampleStreamFactory
Note: Do not use this class, internal use only!
OutcomePriorFeatureGenerator
The definition feature maps the underlying distribution of outcomes.
ParagraphStream
A `FilterObjectStream` which merges text lines into paragraphs.
ParallelNegLogLikelihood
Evaluates `negative log-likelihood` and its gradient in parallel.
Parse
Data structure for holding parse constituents.
Parser
A shift reduce style `Parser` implementation based on Adwait Ratnaparkhi's 1998 thesis.
Parser
Defines common methods for full-syntactic parsers.
Parser
A built-attach `Parser` implementation.
ParserChunkerFactory
ParserChunkerSequenceValidator
The parser chunker `SequenceValidator` implementation.
ParserConverterTool
Tool to convert multiple data formats into native OpenNLP parser format.
ParserCrossValidator
Cross validator for a `Parser`.
ParserEvaluationMonitor
A marker interface for evaluating `parsers`.
ParserEvaluator
This implementation of `Evaluator<Parse>` behaves like `EVALB` with no exceptions, e.g, without removing punctuation tags, or equality between `ADVP` and `PRT`, as in COLLINS convention.
ParserEvaluatorTool
A default `Parse`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
ParserEventStream
Wrapper class for one of four `shift-reduce parser` event streams.
ParserEventStream
Wrapper class for one of four `built-attach parser` event streams.
ParserEventTypeEnum
Enumeration of event types for a `Parser`.
ParserFactory
ParserModel
This is the default `ParserModel` implementation.
ParserModelLoader
Loads a `ParserModel` for the command line tools.
ParserTool
ParserTrainerTool
ParserType
Enumeration of supported `Parser` types.
ParseSampleStream
ParseSampleStreamFactory
Factory producing OpenNLP `ParseSampleStream`s.
ParseSampleStreamFactory.Parameters
ParseToPOSSampleStream
Note: Do not use this class, internal use only!
ParseToPOSSampleStreamFactory
Note: Do not use this class, internal use only!
ParseToPOSSampleStreamFactory.Parameters
ParseToSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
ParseToSentenceSampleStreamFactory.Parameters
ParseToTokenSampleStreamFactory
Note: Do not use this class, internal use only!
ParseToTokenSampleStreamFactory.Parameters
PerceptronModel
A `model` implementation based one the perceptron algorithm.
PerceptronModelReader
The base class for readers of `models`.
PerceptronModelWriter
The base class for `PerceptronModel` writers.
PerceptronTrainer
Trains `models` using the perceptron algorithm.
PlainTextByLineStream
Reads a plain text file and returns each line as a `String` object.
PlainTextFileDataReader
A generic `DataReader` implementation for plain text files.
PlainTextNaiveBayesModelReader
A `NaiveBayesModelReader` that reads models from a plain text format.
PlainTextNaiveBayesModelWriter
A `NaiveBayesModelWriter` that writes models in a plain text format.
porterStemmer
This class implements the stemming algorithm defined by a snowball script.
PorterStemmer
A `Stemmer`, implementing the Porter Stemming Algorithm
PortugueseContractionUtility
Utility class to handle Portuguese contractions.
portugueseStemmer
This class implements the stemming algorithm defined by a snowball script.
POSContextGenerator
Interface for a `BeamSearchContextGenerator` used in POS tagging.
POSDictionary
Provides a means of determining which tags are valid for a particular word based on a `TagDictionary` read from a file.
POSEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
POSEvaluator
The `POSEvaluator` measures the performance of the given `POSTagger` with the provided reference `samples`.
POSModel
The `POSModel` is the model used by a learnable `POSTagger`.
POSModelLoader
Loads a `POSModel` for the command line tools.
POSModelSerializer
An `ArtifactSerializer` implementation for `models`.
POSSample
Represents an pos-tagged `sentence`.
POSSampleEventStream
Reads the `samples` from an `Iterator` and converts those samples into `events` which can be used by the maxent library for training.
POSSampleSequenceStream
A `SequenceStream` implementation encapsulating `samples`.
PosSampleStream
POSTagFormat
Defines the format for part-of-speech tagging, i.e.
POSTagFormatMapper
A mapping implementation for converting between different POS tag formats.
POSTagFormatMapper.NoOp
POSTagger
The interface for part of speech taggers.
POSTaggerConverterTool
Tool to convert multiple data formats into native OpenNLP part of speech tagging training format.
POSTaggerCrossValidator
POSTaggerCrossValidatorTool
POSTaggerEvaluationMonitor
A marker interface for evaluating `pos taggers`.
POSTaggerEvaluatorTool
A default `POSSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
POSTaggerFactory
The factory that provides `POSTagger` default implementations and resources.
POSTaggerFactory.POSDictionarySerializer
PosTaggerFeatureGenerator
A POS tagging driven feature generator.
PosTaggerFeatureGeneratorFactory
A `GeneratorFactory` that produces `PosTaggerFeatureGenerator` instances when `PosTaggerFeatureGeneratorFactory.create()` is called.
POSTaggerFineGrainedReportListener
Generates a detailed report for the POS Tagger.
POSTaggerME
A `part-of-speech tagger` implementation that uses maximum entropy.
POSTaggerNameFeatureGenerator
Adds the token POS tag as feature.
POSTaggerNameFeatureGeneratorFactory
A `GeneratorFactory` that produces `POSTaggerNameFeatureGenerator` instances when `POSTaggerNameFeatureGeneratorFactory.create()` is called.
POSTaggerTool
POSTaggerTrainerTool
POSToSentenceSampleStream
Note: Do not use this class, internal use only!
POSToSentenceSampleStreamFactory
Note: Do not use this class, internal use only!
POSToSentenceSampleStreamFactory.Parameters
POSToTokenSampleStream
Note: Do not use this class, internal use only!
POSToTokenSampleStreamFactory
Note: Do not use this class, internal use only!
POSToTokenSampleStreamFactory.Parameters
PrefixFeatureGenerator
A feature generator implementation that generates prefix-based features.
PrefixFeatureGeneratorFactory
A `GeneratorFactory` that produces `PrefixFeatureGenerator` instances when `PrefixFeatureGeneratorFactory.create()` is called.
PreviousMapFeatureGenerator
This `AdaptiveFeatureGenerator` generates features indicating the outcome associated with a previously occurring word.
PreviousMapFeatureGeneratorFactory
A `GeneratorFactory` that produces `PreviousMapFeatureGenerator` instances when `PreviousMapFeatureGeneratorFactory.create()` is called.
PreviousTwoMapFeatureGenerator
This `AdaptiveFeatureGenerator` generates features indicating the outcome associated with two previously occurring words.
Prior
This interface allows one to implement a prior distribution for use in maximum entropy model training.
Probabilistic
A marker interface for classes with probabilistic capabilities.
Probabilities<T>
Class implementing the probability distribution over labels returned by a classifier.
Probability<T>
Class implementing the probability for a label.
ProbingLanguageDetectionResult
A data container encapsulating language detection results.
QNMinimizer
Implementation of the Limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) which supports L1-, L2-regularization and Elastic Net for solving convex optimization problems.
QNMinimizer.Evaluator
Evaluate the quality of training parameters.
QNMinimizer.L2RegFunction
L2-regularized objective `Function`.
QNModel
A `maximum entropy model` which has been trained via the L-BFGS algorithm , which belongs to the group of Quasi Newton (QN) algorithms.
QNModelReader
The base class for readers of `QN models`.
QNModelWriter
The base class for writers of `models`.
QNTrainer
A Maxent model `trainer` using the L-BFGS algorithm.
RealBasicEventStream
Class for real-valued `events` as an `event stream`. .
RealValueFileEventStream
Class for using a file of real-valued `events` as an `event stream`.
RegexNameFinder
A `TokenNameFinder` implementation based on a series of regular expressions.
RegexNameFinderFactory
Returns a `RegexNameFinder` based on a selection of defaults or a configuration and a selection of defaults.
RegexNameFinderFactory.DEFAULT_REGEX_NAME_FINDER
Enumeration of typical regex expressions available in OpenNLP.
RegexNameFinderFactory.RegexAble
RelationAnnotation
ResetableIterator<E>
This interface makes an `Iterator` resettable.
ReverseListIterator<T>
An iterator for a list which returns values in the opposite order as the typical list iterator.
romanianStemmer
This class implements the stemming algorithm defined by a snowball script.
russianStemmer
This class implements the stemming algorithm defined by a snowball script.
Sample
Represents a generic type of processable elements.
SDContextGenerator
Interface for `SentenceDetectorME` context generators.
SDCrossValidator
A cross validator for `sentence detectors`.
SDEventStream
SegmenterObjectStream<S,T>
SentenceContextGenerator
Creates contexts/features for end-of-sentence detection in Thai text.
SentenceDetector
The interface for sentence detectors, which find the sentence boundaries in a text.
SentenceDetectorConverterTool
Tool to convert multiple data formats into native OpenNLP sentence detector training format.
SentenceDetectorCrossValidatorTool
SentenceDetectorEvaluationMonitor
SentenceDetectorEvaluator
The `SentenceDetectorEvaluator` measures the performance of the given `SentenceDetector` with the provided reference `SentenceSample`s.
SentenceDetectorEvaluatorTool
A default `SentenceSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
SentenceDetectorFactory
The factory that provides `SentenceDetector` default implementations and resources
SentenceDetectorME
A sentence detector for splitting up raw text into sentences.
SentenceDetectorTool
A sentence detector which uses a maxent model to predict the sentences.
SentenceDetectorTrainerTool
SentenceEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
SentenceFeatureGenerator
This feature generator creates sentence begin and end features.
SentenceFeatureGeneratorFactory
A `GeneratorFactory` that produces `SentenceFeatureGenerator` instances when `SentenceFeatureGeneratorFactory.create()` is called.
SentenceModel
The `SentenceModel` is the model used by a learnable `SentenceDetector`.
SentenceSample
A `SentenceSample` contains a document with begin indexes of the individual sentences.
SentenceSampleStream
This class is a stream filter which reads a sentence by line samples from an `ObjectStream` and converts them into `SentenceSample` objects.
SentenceSampleStreamFactory
Factory producing OpenNLP `SentenceSampleStream`s.
SentenceSampleStreamFactory.Parameters
Sequence<T>
Class which models a sequence.
Sequence
Represents a weighted sequence of outcomes.
SequenceClassificationModel
A classification model that can label an input `Sequence`.
SequenceCodec<T>
A codec for sequences of type `SequenceCodec`.
SequenceStream<S>
Interface for streams of `sequences` used to train sequence models.
SequenceStreamEventStream
Class which turns a `SequenceStream` into an event stream.
SequenceTrainer
SequenceValidator<T>
SerializableArtifact
A marker interface so that implementing classes can refer to the corresponding `ArtifactSerializer` implementation.
SgmlParser
A SAX style SGML parser.
SgmlParser.ContentHandler
Defines methods to handle content produced by a `SgmlParser`.
ShrinkCharSequenceNormalizer
A `ShrinkCharSequenceNormalizer` implementation that shrinks repeated spaces / chars in text.
SimplePerceptronSequenceTrainer
Trains `models` with sequences using the perceptron algorithm.
SimpleTokenizer
A basic `Tokenizer` implementation which performs tokenization using character classes.
SimpleTokenizerTool
SnowballProgram
Base class for a snowball stemmer
SnowballStemmer
SnowballStemmer.ALGORITHM
Span
Class for storing start and end integer offsets.
SpanAnnotation
spanishStemmer
This class implements the stemming algorithm defined by a snowball script.
Stemmer
The stemmer is reducing a word to its stem.
StopCriteria<T>
Stop criteria for model training.
StringInterner
A marker-interface for a String interner implementation.
StringInterners
Provides string interning utility methods.
StringList
A `StringList` is an immutable list of `String`s.
StringPattern
Recognizes predefined patterns in strings.
StringUtil
SuffixFeatureGenerator
A feature generator implementation that generates suffix-based features.
SuffixFeatureGeneratorFactory
A `GeneratorFactory` that produces `SuffixFeatureGenerator` instances when `SuffixFeatureGeneratorFactory.create()` is called.
swedishStemmer
This class implements the stemming algorithm defined by a snowball script.
TagDictionary
Interface to determine which tags are valid for a particular word based on a tag dictionary.
TaggerModelReplacerTool
ThreadSafe
Classes, fields, or methods annotated `&#64;ThreadSafe` are safe to use in multithreading contexts.
ThreadSafeChunkerME
A thread-safe version of the `ChunkerME`.
ThreadSafeLanguageDetectorME
A thread-safe version of the `LanguageDetectorME`.
ThreadSafeLemmatizerME
A thread-safe version of the `LemmatizerME`.
ThreadSafeNameFinderME
A thread-safe version of `NameFinderME`.
ThreadSafePOSTaggerME
A thread-safe version of the `POSTaggerME`.
ThreadSafeSentenceDetectorME
A thread-safe version of `SentenceDetectorME`.
ThreadSafeTokenizerME
A thread-safe version of `TokenizerME`.
TokenClassFeatureGenerator
Generates features for the class of a token.
TokenClassFeatureGeneratorFactory
A `GeneratorFactory` that produces `TokenClassFeatureGenerator` instances when `TokenClassFeatureGeneratorFactory.create()` is called.
TokenContextGenerator
Interface for context generators required for `TokenizerME`.
TokenEvaluationErrorListener
A default implementation of `EvaluationMonitor` that prints to an output stream.
TokenFeatureGenerator
Generates a feature which contains a token itself.
TokenFeatureGeneratorFactory
A `GeneratorFactory` that produces `TokenFeatureGenerator` instances when `TokenFeatureGeneratorFactory.create()` is called.
Tokenizer
The interface for tokenizers, which segment a string into its tokens.
TokenizerConverterTool
Tool to convert multiple data formats into native OpenNLP sentence detector training format.
TokenizerCrossValidator
A cross validator for `tokenizers`.
TokenizerCrossValidatorTool
TokenizerEvaluationMonitor
A marker interface for evaluating `tokenizers`.
TokenizerEvaluator
The `TokenizerEvaluator` measures the performance of the given `Tokenizer` with the provided reference `samples`.
TokenizerFactory
The factory that provides `Tokenizer` default implementation and resources.
TokenizerME
A `Tokenizer` for converting raw text into separated tokens.
TokenizerMEEvaluatorTool
A default `TokenSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
TokenizerMETool
TokenizerModel
The `TokenizerModel` is the model used by a learnable `Tokenizer`.
TokenizerModelLoader
Loads a `TokenizerModel` for the command line tools.
TokenizerStream
The `TokenizerStream` uses a `Tokenizer` to tokenize the input string and output `samples`.
TokenizerTrainerTool
TokenNameFinder
The interface for name finders which provide name tags for a sequence of tokens.
TokenNameFinderConverterTool
Tool to convert multiple data formats into native OpenNLP name finder training format.
TokenNameFinderCrossValidator
Cross validator for `TokenNameFinder`.
TokenNameFinderCrossValidatorTool
TokenNameFinderDetailedFMeasureListener
TokenNameFinderEvaluationMonitor
A marker interface for evaluating `name finders`.
TokenNameFinderEvaluator
The `TokenNameFinderEvaluator` measures the performance of the given `TokenNameFinder` with the provided reference `samples`.
TokenNameFinderEvaluatorTool
A default `NameSample`-centric implementation of `AbstractEvaluatorTool` that prints to an output stream.
TokenNameFinderFactory
The factory that provides `TokenNameFinder` default implementations and resources.
TokenNameFinderFineGrainedReportListener
Generates a detailed report for the NameFinder.
TokenNameFinderModel
The `TokenNameFinderModel` is the model used by a learnable `TokenNameFinder`.
TokenNameFinderModel.FeatureGeneratorCreationError
TokenNameFinderModelLoader
Loads a `TokenNameFinderModel` for the command line tools.
TokenNameFinderTool
TokenNameFinderTrainerTool
TokenPatternFeatureGenerator
Partitions tokens into sub-tokens based on character classes and generates class features for each of the sub-tokens and combinations of those sub-tokens.
TokenPatternFeatureGeneratorFactory
A `GeneratorFactory` instantiates `TokenPatternFeatureGenerator` instances when `TokenPatternFeatureGeneratorFactory.create()` is called.
TokenSample
A `TokenSample` is text with token spans.
TokenSampleStream
Class which produces an Iterator<TokenSample> from a file of space delimited token.
TokenSampleStream
This class is a `stream filter` which reads in string encoded samples and creates `samples` out of them.
TokenSampleStreamFactory
Factory producing OpenNLP `TokenSampleStream`s.
TokenSampleStreamFactory.Parameters
TokenTag
TokSpanEventStream
This class reads the `samples` via an `Iterator` and converts the samples into `events` which can be used by the maxent library for training.
Trainer
Represents a common base for training implementations.
TrainerFactory
A factory to initialize `Trainer` instances depending on a trainer type configured via `TrainingParameters`.
TrainerFactory.TrainerType
TrainingConfiguration
Configuration used for `AbstractModel` training.
TrainingMeasure
Enumeration of Training measures.
TrainingParameters
Declares and handles default parameters used for or during training models.
TrainingProgressMonitor
An interface to capture training progress of an `AbstractModel`.
TrainingToolParams
Common training parameters.
TrigramNameFeatureGenerator
Adds trigram features based on tokens and token classes.
TrigramNameFeatureGeneratorFactory
A `GeneratorFactory` that produces `TrigramNameFeatureGenerator` instances when `TrigramNameFeatureGeneratorFactory.create()` is called.
turkishStemmer
This class implements the stemming algorithm defined by a snowball script.
TwentyNewsgroupSampleStream
An `ObjectStream` implementation for the Twenty Newsgroups text corpus.
TwentyNewsgroupSampleStreamFactory
Note: Do not use this class, internal use only!
TwentyNewsgroupSampleStreamFactory.Parameters
TwitterCharSequenceNormalizer
A `TwitterCharSequenceNormalizer` implementation that normalizes text in terms of Twitter character patterns.
TwoPassDataIndexer
Collecting event and context counts by making two passes over the events.
UncloseableInputStream
An `InputStream` which cannot be closed.
UniformPrior
Provide a maximum entropy model with a uniform `Prior`.
UrlCharSequenceNormalizer
A `UrlCharSequenceNormalizer` implementation that normalizes text in terms of URls and email addresses.
Version
The `Version` class represents the OpenNLP Tools library version.
WhitespaceTokenizer
A basic `Tokenizer` implementation which performs tokenization using white spaces.
WhitespaceTokenStream
This stream formats `ObjectStream` of `samples` into whitespace separated token strings.
WindowFeatureGenerator
Generates previous (left-sided) and next (right-sided) features for a given `AdaptiveFeatureGenerator`.
WindowFeatureGeneratorFactory
A `GeneratorFactory` that produces `WindowFeatureGenerator` instances when `WindowFeatureGeneratorFactory.create()` is called.
WordClusterDictionary
WordClusterDictionary.WordClusterDictionarySerializer
WordClusterFeatureGenerator
An `AdaptiveFeatureGenerator` implementation of a word cluster feature generator.
WordClusterFeatureGeneratorFactory
Defines a word cluster `GeneratorFactory`; it reads an element containing 'w2vwordcluster' as a tag name.
WordpieceTokenizer
A `Tokenizer` implementation which performs tokenization using word pieces.
WordTagSampleStream
A `stream filter` which reads a sentence per line that contains words and tags in `word_tag` format and outputs a `POSSample` objects.
WordTagSampleStreamFactory
Note: Do not use this class, internal use only!
WordTagSampleStreamFactory.Parameters
WordVector
A word vector.
WordVectorTable
A table that maps tokens to word vectors.
WordVectorType
XmlUtil