# All Classes and Interfaces

Class
Description
AbstractObjectStream<T>
A base `ObjectStream` implementation.
AdaptiveFeatureGenerator
An interface for generating features for name entity identification and for updating document level contexts.
AlgorithmType
AlignedText
The result of a normalization that keeps the original text alongside the normalized form and a full `Alignment` between them.
Alignment
A bidirectional alignment between an original text and a normalized form of it.
Alignment.Builder
Builds an `Alignment` as the normalized text is produced, by recording each edit in order.
ArgumentParser
Parser for command line arguments.
ArgumentParser.OptionalParameter
ArgumentParser.ParameterDescription
ArrayMath
Utility class for simple vector arithmetic.
ArtifactProvider
Provides access to model persisted artifacts.
ArtifactSerializer<T>
Responsible to create an artifact from an `InputStream`.
BaseLink
Represents a minimal tuple of information.
BasicFormatParams
Common format parameters.
BasicTrainingParams
Common training parameters.
BeamSearchContextGenerator<T>
Interface for context generators used with a sequence beam search.
BertTokenizer
A `Tokenizer` implementation of the full BERT tokenization pipeline: basic tokenization (text normalization) followed by wordpiece tokenization.
Cache<K,V>
Provides fixed size, pre-allocated, least recently used replacement cache.
CharClass
A configurable class of Unicode code points and the cursor based operations over it.
CharSequenceNormalizer
A char sequence normalizer, used to adjusting (prune, substitute, add, etc.)
Chunker
The interface for chunkers which provide chunk tags for a sequence of tokens.
ChunkerContextGenerator
Interface for a `BeamSearchContextGenerator` used in syntactic chunking.
ChunkerEvaluationMonitor
A marker interface for evaluating `chunkers`.
ChunkSample
Class for holding chunks for a single unit of text.
ClassPathLoaderException
ClassPathModelEntry
Encapsulates a classpath entry that is associated with a `model URI` and optional `properties`.
ClassPathModelFinder
Describes a scanner which detects OpenNLP specific model files in an applications's classpath.
CodePointSet
An immutable set of Unicode code points with O(1) membership.
Constituent
Holds constituents when reading `parses`.
Context
Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
CVParams
Common cross validator parameters.
DataIndexer<P>
Represents an indexer which compresses events in memory and performs feature selection.
DataReader
Describes generic ways to read data from a `DataInputStream`.
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.
DetokenizerParameter
DoccatEvaluationMonitor
A marker interface for evaluating `doccat`.
DocumentCategorizer
Interface for classes which categorize documents.
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.
EncodingParameter
Encoding parameter.
EndOfSentenceScanner
Scans `CharSequence`, `StringBuffer`, and `char[]` for the offsets of sentence ending characters.
EntityLinker<T>
EntityLinkers establish connections with external data to enrich extracted entities.
EntityLinkerProperties
Properties wrapper for `EntityLinker` implementations.
EvaluationMonitor<T>
EvaluatorParams
Common evaluation parameters.
Event
The context of a decision point during training.
EventModelSequenceTrainer<T,P>
A specialized `Trainer` that is based on a 'EventModelSequence' approach.
EventTrainer<P>
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
FeatureGenerator
Interface for generating features for document categorization.
FeatureGeneratorResourceProvider
The `FeatureGeneratorResourceProvider` provides access to the resources available in the model.
FineGrainedEvaluatorParams
Common evaluation parameters.
FMeasure
The `FMeasure` is a utility class for `evaluators` which measures precision, recall and the resulting f-measure.
GapLabeler
Represents a labeler for nodes which contain traces so that these traces can be predicted by a `Parser`.
HeadRules
Encoder for head rules associated with parsing.
InputStreamFactory
Allows repeated reads through a stream for certain model building types.
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.
Language
Class for holding the document language and its confidence
LanguageCodeValidator
Validates language codes against ISO 639 standards.
LanguageDetector
The interface for `LanguageDetector` which predicts the `Language` for a context.
LanguageDetectorContextGenerator
A context generator interface for `LanguageDetector`.
LanguageDetectorEvaluationMonitor
A marker interface for evaluating `language detectors`.
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`.
LemmaSample
Represents a lemmatized sentence.
Lemmatizer
The common interface for lemmatizers.
LemmatizerContextGenerator
Interface for the context generator used for probabilistic `Lemmatizer`.
LemmatizerEvaluationMonitor
A marker interface for evaluating `lemmatizers`.
LinkedSpan<T>
A default, extended `Span` that holds additional information about a `Span`.
MaxentModel
Interface for maximum entropy models.
Mean
Calculates the arithmetic mean of values added with the `Mean.add(double)` method.
ModelType
A model type to pattern enumeration.
ModelType
Enumeration of supported model types.
MutableTagDictionary
Interface that allows `TagDictionary` entries to be added and removed.
NameContextGenerator
Interface for generating the context for a `name finder` by specifying a set of feature generators.
NameSample
Encapsulates names for a single unit of text.
ObjectStream<T>
Reads `objects` from a stream.
ObjectStreamFactory<T,P>
ObjectStreamUtils
OffsetAwareNormalizer
A `CharSequenceNormalizer` that can additionally report the `Alignment` from its normalized output back to the input, so a span found in the normalized text maps to the exact character offsets of the original.
OffsetMappingNameFinder
A `TokenNameFinder` that can additionally report detected spans in the character coordinates of the original input, mapping back through any text normalization applied before detection.
Parameters
Parse
Data structure for holding parse constituents.
Parser
Defines common methods for full-syntactic parsers.
ParserEvaluationMonitor
A marker interface for evaluating `parsers`.
ParserEventTypeEnum
Enumeration of event types for a `Parser`.
ParserType
Enumeration of supported `Parser` types.
PlainTextByLineStream
Reads a plain text file and returns each line as a `String` object.
POSContextGenerator
Interface for a `BeamSearchContextGenerator` used in POS tagging.
POSSample
Represents an pos-tagged `sentence`.
POSTagger
The interface for part of speech taggers.
POSTaggerEvaluationMonitor
A marker interface for evaluating `pos taggers`.
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.
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 `SentenceDetector` context generators.
SentenceDetector
The interface for sentence detectors, which find the sentence boundaries in a text.
SentenceDetectorEvaluationMonitor
SentenceSample
A `SentenceSample` contains a document with begin indexes of the individual sentences.
SentimentDetector
SentimentEvaluationMonitor
An sentiment specific `EvaluationMonitor` to be used by the evaluator.
SentimentSample
Class for holding text used for sentiment analysis.
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.
SequenceTrainer<P>
SequenceValidator<T>
SerializableArtifact
A marker interface so that implementing classes can refer to the corresponding `ArtifactSerializer` implementation.
Span
Class for storing start and end integer offsets.
Stemmer
Reduces a word to its root form.
StemmerFactory
A factory that captures a stemmer configuration and mints configured `Stemmer` instances on demand.
StopCriteria<T>
Stop criteria for model training.
StopwordFilter
A pluggable filter that decides whether a token (or a sequence of tokens) is a stopword that should be removed during downstream text processing.
StringInterner
A marker-interface for a String interner implementation.
StringUtil
TagDictionary
Interface to determine which tags are valid for a particular word based on a tag dictionary.
TerminateToolException
Exception to terminate the execution of a command line tool.
ThreadSafe
Classes, fields, or methods annotated `&#64;ThreadSafe` are safe to use in multithreading contexts.
TokenContextGenerator
Interface for context generators required for `tokenizer implementations`.
Tokenizer
The interface for tokenizers, which segment a string into its tokens.
TokenizerEvaluationMonitor
A marker interface for evaluating `tokenizers`.
TokenNameFinder
The interface for name finders which provide name tags for a sequence of tokens.
TokenNameFinderEvaluationMonitor
A marker interface for evaluating `name finders`.
TokenSample
A `TokenSample` is text with token spans.
TokenTag
Trainer<P>
Represents a common base for training implementations.
TrainingConfiguration
Configuration used for model training.
TrainingMeasure
Enumeration of Training measures.
TrainingProgressMonitor
An interface to capture training progress of a model.
TrainingToolParams
Common training parameters.
UnicodeDash
Reference data for Unicode dashes, plus O(1) membership lookups.
UnicodeDash.Category
The Unicode general category of a dash code point.
UnicodeDash.DashCharacter
One Unicode dash code point and its reference attributes.
UnicodeWhitespace
Reference data for Unicode whitespace, plus O(1) membership lookups.
UnicodeWhitespace.Breaking
Line-breaking behavior, mirroring the "Notes" column of the reference table.
UnicodeWhitespace.Category
Unicode general category for a whitespace or related code point.
UnicodeWhitespace.RelatedCharacter
One related code point that is commonly confused with whitespace but is not (`White_Space=no`).
UnicodeWhitespace.WhitespaceCharacter
One Unicode whitespace code point and its reference attributes.
WhitespaceMode
Selects the whitespace definition used by `StringUtil.isWhitespace(char)` and `StringUtil.isWhitespace(int)`: the Unicode `White_Space` property, or OpenNLP's legacy definition from 1.x/2.x.
WhitespaceTokenizer
A basic `Tokenizer` implementation which performs tokenization using white spaces.
WordpieceTokenizer
A `Tokenizer` implementation which performs tokenization using word pieces.
WordVector
A word vector.
WordVectorTable
A table that maps tokens to word vectors.
WordVectorType