# All Classes

- All Classes Interface Summary Class Summary Enum Summary Exception Summary Annotation Types Summary
  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.
  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<P> | A Factory to create a Arvores Deitadas ChunkStream from the command line utility.
  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<P> | A Factory to create a Arvores Deitadas NameSampleDataStream from the command line utility.
  ADPOSSampleStream | Note: Do not use this class, internal use only!
  ADPOSSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ADSentenceSampleStream | Note: Do not use this class, internal use only!
  ADSentenceSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  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<P> | Note: Do not use this class, internal use only!
  AggregateCharSequenceNormalizer | A `CharSequenceNormalizer` implementation that aggregates the functionality of other normalizers.
  AggregatedFeatureGenerator | The `AggregatedFeatureGenerator` aggregates a set of `AdaptiveFeatureGenerator`s and calls them to generate the features.
  AggregatedFeatureGeneratorFactory |
  AncoraSpanishHeadRules | Class for storing the Ancora Spanish head rules associated with parsing.
  AncoraSpanishHeadRules.HeadRulesSerializer |
  AnnotationConfiguration |
  AnnotatorNoteAnnotation |
  arabicStemmer | This class was automatically generated by a Snowball to Java compiler It implements the stemming algorithm defined by a snowball script.
  ArrayMath | Utility class for simple vector arithmetic.
  ArrayMath | Deprecated.
  ArtifactProvider | Provides access to model persisted artifacts.
  ArtifactSerializer<T> | Responsible to create an artifact from an `InputStream`.
  ArtifactToSerializerMapper | Deprecated.
  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<T> | Performs k-best search over a sequence.
  BeamSearchContextGenerator<T> | Interface for context generators used with a sequence beam search.
  BigramNameFeatureGenerator |
  BigramNameFeatureGeneratorFactory |
  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.
  BioNLP2004NameSampleStream | A `sample stream` for the training files of the BioNLP/NLPBA 2004 shared task.
  BioNLP2004NameSampleStreamFactory<P> |
  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 |
  BrownBigramFeatureGenerator | Generates Brown cluster features for token bigrams.
  BrownCluster | Class to load a Brown cluster document: word\tword_class\tprob
  BrownCluster.BrownClusterSerializer |
  BrownClusterBigramFeatureGeneratorFactory | Generates Brown clustering features for token bigrams.
  BrownClusterTokenClassFeatureGeneratorFactory | Generates Brown clustering features for token classes.
  BrownClusterTokenFeatureGeneratorFactory | Generates Brown clustering features for current token.
  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 |
  catalanStemmer | This class was automatically generated by a Snowball to Java compiler It 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 |
  CharSequenceNormalizer | A char sequence normalizer, used to adjusting (prune, substitute, add, etc.) characters in order to remove noise from text
  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.
  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<P> | Factory producing OpenNLP `ChunkSampleStream`s.
  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<P> | Note: Do not use this class, internal use only!
  Conll03NameSampleStream | An import stream which can parse the CONLL03 data.
  Conll03NameSampleStream.LANGUAGE |
  Conll03NameSampleStreamFactory<P> |
  ConlluLemmaSampleStream |
  ConlluLemmaSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConlluPOSSampleStream |
  ConlluPOSSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConlluSentence |
  ConlluSentenceSampleStream |
  ConlluSentenceSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConlluStream | The CoNNL-U Format is specified here.
  ConlluTagset |
  ConlluTokenSampleStream |
  ConlluTokenSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConlluWordLine |
  ConllXPOSSampleStream | Parses the data from the CONLL 06 shared task into POS Samples.
  ConllXPOSSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConllXSentenceSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  ConllXTokenSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  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.
  CustomFeatureGenerator | Deprecated.
  CVParams | Common cross validator parameters.
  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.
  DefinitionFeatureGeneratorFactory |
  DetailedFMeasureEvaluatorParams | EvaluatorParams for Chunker.
  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 the `DictionaryNameFinder` to generated features for detected names based on the `InSpanGenerator`.
  DictionaryFeatureGeneratorFactory |
  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` 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 |
  DocumentBeginFeatureGeneratorFactory |
  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<P> | Factory producing OpenNLP `DocumentSampleStream`s.
  DocumentToLineStream | Reads a plain text file and return each line as a `String` object.
  DownloadUtil | This class facilitates the downloading of pretrained OpenNLP models.
  DownloadUtil.ModelType | The type of model.
  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.
  EntityLinker<T extends Span> | 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<P> | Note: Do not use this class, internal use only!
  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.
  FMeasure | The `FMeasure` is a utility class for `evaluators` which measures precision, recall and the resulting f-measure.
  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.
  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 was automatically generated by a Snowball to Java compiler It implements the stemming algorithm defined by a snowball script.
  HashSumEventStream | A hash sum based `AbstractObjectStream` implementation.
  HeadRules | Encoder for head rules associated with parsing.
  HeadRules | Class for storing the English `HeadRules` associated with parsing.
  HeadRules.HeadRulesSerializer |
  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<P> |
  IrishSentenceBankTokenSampleStreamFactory<P> |
  irishStemmer | This class was automatically generated by a Snowball to Java compiler It implements the stemming algorithm defined by a snowball script.
  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<P> | Factory producing OpenNLP `DocumentSampleStream`s.
  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<P> | Note: Do not use this class, internal use only!
  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<P> | Factory producing OpenNLP `LemmaSampleStream`s.
  LemmatizerTrainerTool |
  LetsmtDocument | A structure to hold the letsmt document.
  LetsmtDocument.LetsmtDocumentHandler | A `content handler` to receive and process SAX events.
  LetsmtDocument.LetsmtSentence |
  LetsmtSentenceStreamFactory<P> |
  LineSearch | Class that performs line search to find minimum.
  LineSearch.LineSearchResult | Represents a LineSearch result.
  LinkedSpan<T extends BaseLink> | A default, extended `Span` that holds additional information about a `Span`.
  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`
  MascDocument |
  MascDocumentStream |
  MascNamedEntityParser | A class to process the MASC Named entity stand-off annotation file
  MascNamedEntitySampleStream |
  MascNamedEntitySampleStreamFactory<P> |
  MascPennTagParser | A class for parsing MASC's Penn tagging/tokenization stand-off annotation
  MascPOSSampleStream |
  MascPOSSampleStreamFactory<P> |
  MascSentence |
  MascSentenceSampleStream |
  MascSentenceSampleStreamFactory<P> |
  MascToken | A specialized `Span` to express tokens in `documents`.
  MascTokenSampleStream |
  MascTokenSampleStreamFactory<P> |
  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 | Enumeration of supported model types.
  ModelUtil | Utility class for handling of `models`.
  MosesSentenceSampleStream |
  MosesSentenceSampleStreamFactory<P> | Factory producing OpenNLP `MosesSentenceSampleStream` objects.
  Muc6NameSampleStreamFactory |
  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 `strings` provided by a `DataStream` to `NameSample` objects.
  NameSampleDataStreamFactory<P> | 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<P> | Note: Do not use this class, internal use only!
  NameToTokenSampleStream | Note: Do not use this class, internal use only!
  NameToTokenSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  NegLogLikelihood | Evaluate 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<P> |
  NKJPTextDocument | The National corpus of Polish (NKJP) format.
  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 corpus.
  OntoNotesNameSampleStreamFactory |
  OntoNotesParseSampleStream |
  OntoNotesParseSampleStreamFactory |
  OntoNotesPOSSampleStreamFactory |
  OutcomePriorFeatureGenerator | The definition feature maps the underlying distribution of outcomes.
  ParagraphStream | A `FilterObjectStream` which merges text lines into paragraphs.
  ParallelNegLogLikelihood | Evaluate 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` 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<P> | 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!
  ParseToSentenceSampleStreamFactory | Note: Do not use this class, internal use only!
  ParseToTokenSampleStreamFactory | Note: Do not use this class, internal use only!
  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 | A `Stemmer`, implementing the Porter Stemming Algorithm
  PortugueseContractionUtility | Utility class to handle Portuguese contractions.
  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 |
  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 |
  PosTaggerFeatureGeneratorFactory |
  POSTaggerFineGrainedReportListener | Generates a detailed report for the POS Tagger.
  POSTaggerME | A `part-of-speech tagger` that uses maximum entropy.
  POSTaggerNameFeatureGenerator | Adds the token POS Tag as feature.
  POSTaggerNameFeatureGeneratorFactory |
  POSTaggerTool |
  POSTaggerTrainerTool |
  POSToSentenceSampleStream | Note: Do not use this class, internal use only!
  POSToSentenceSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  POSToTokenSampleStream | Note: Do not use this class, internal use only!
  POSToTokenSampleStreamFactory<P> | Note: Do not use this class, internal use only!
  PrefixFeatureGenerator |
  PrefixFeatureGeneratorFactory |
  PreviousMapFeatureGenerator | This `AdaptiveFeatureGenerator` generates features indicating the outcome associated with a previously occurring word.
  PreviousMapFeatureGeneratorFactory |
  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.
  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 L-BFGS which supports L1-, L2-regularization and Elastic Net for solving convex optimization problems.
  QNMinimizer.Evaluator | Evaluate quality of training parameters.
  QNMinimizer.L2RegFunction | L2-regularized objective `Function`.
  QNModel | A maximum entropy model which has been trained using the Quasi Newton (QN) algorithm.
  QNModelReader | The base class for readers of `QN models`.
  QNModelWriter | The base class for writers of `models`.
  QNTrainer | A Maxent model `Trainer` using 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.
  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 |
  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<P> | Factory producing OpenNLP `SentenceSampleStream`s.
  Sequence<T> | Class which models a sequence.
  Sequence | Represents a weighted sequence of outcomes.
  SequenceClassificationModel<T> | 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 | SAX style SGML parser.
  SgmlParser.ContentHandler |
  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 |
  SnowballStemmer |
  SnowballStemmer.ALGORITHM |
  Span | Class for storing start and end integer offsets.
  SpanAnnotation |
  Stemmer | The stemmer is reducing a word to its stem.
  StringList | A `StringList` is an immutable list of `String`s.
  StringPattern | Recognizes predefined patterns in strings.
  StringUtil |
  SuffixFeatureGenerator |
  SuffixFeatureGeneratorFactory |
  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.
  TokenClassFeatureGenerator | Generates features for different for the class of the token.
  TokenClassFeatureGeneratorFactory |
  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 the token itself.
  TokenFeatureGeneratorFactory |
  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 |
  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<P> | Factory producing OpenNLP `TokenSampleStream`s.
  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 |
  TrainingParameters | Declares and handles default parameters used for or during training models.
  TrainingToolParams | Common training parameters.
  TrigramNameFeatureGenerator | Adds trigram features based on tokens and token classes.
  TrigramNameFeatureGeneratorFactory |
  TwentyNewsgroupSampleStream |
  TwentyNewsgroupSampleStreamFactory<P> |
  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 and next features for a given `AdaptiveFeatureGenerator`.
  WindowFeatureGeneratorFactory |
  WordClusterDictionary |
  WordClusterDictionary.WordClusterDictionarySerializer |
  WordClusterFeatureGenerator |
  WordClusterFeatureGeneratorFactory | Defines a word cluster generator factory; it reads an element containing 'w2vwordcluster' as a tag name; these clusters are typically produced by word2vec or clark pos induction systems.
  WordpieceTokenizer | A `Tokenizer` implementation which performs tokenization using word pieces.
  WordTagSampleStream | A stream filter which reads a sentence per line which contains words and tags in `word_tag` format and outputs a `POSSample` objects.
  WordTagSampleStreamFactory<P> | 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 |