All Classes and Interfaces

Class
Description
A base ObjectStream implementation.
An interface for generating features for name entity identification and for updating document level contexts.
 
The result of a normalization that keeps the original text alongside the normalized form and a full Alignment between them.
A bidirectional alignment between an original text and a normalized form of it.
Builds an Alignment as the normalized text is produced, by recording each edit in order.
Parser for command line arguments.
 
 
Utility class for simple vector arithmetic.
Provides access to model persisted artifacts.
Responsible to create an artifact from an InputStream.
Represents a minimal tuple of information.
Common format parameters.
Common training parameters.
Interface for context generators used with a sequence beam search.
A Tokenizer implementation of the full BERT tokenization pipeline: basic tokenization (text normalization) followed by wordpiece tokenization.
Provides fixed size, pre-allocated, least recently used replacement cache.
A configurable class of Unicode code points and the cursor based operations over it.
A char sequence normalizer, used to adjusting (prune, substitute, add, etc.)
The interface for chunkers which provide chunk tags for a sequence of tokens.
Interface for a BeamSearchContextGenerator used in syntactic chunking.
A marker interface for evaluating chunkers.
Class for holding chunks for a single unit of text.
 
Encapsulates a classpath entry that is associated with a model URI and optional properties.
Describes a scanner which detects OpenNLP specific model files in an applications's classpath.
An immutable set of Unicode code points with O(1) membership.
Holds constituents when reading parses.
Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
Common cross validator parameters.
Represents an indexer which compresses events in memory and performs feature selection.
Describes generic ways to read data from a DataInputStream.
A Detokenizer merges tokens back to their detokenized representation.
This enum contains an operation for every token to merge the tokens together to their detokenized form.
 
A marker interface for evaluating doccat.
Interface for classes which categorize documents.
Interface for processing an entire document allowing a TokenNameFinder to use context from the entire document.
Class which holds a classified document and its category.
Encoding parameter.
Scans CharSequence, StringBuffer, and char[] for the offsets of sentence ending characters.
EntityLinkers establish connections with external data to enrich extracted entities.
Properties wrapper for EntityLinker implementations.
 
Common evaluation parameters.
The context of a decision point during training.
A specialized Trainer that is based on a 'EventModelSequence' approach.
A specialized Trainer that is based on an Event approach.
Indicates that a certain API feature is not stable and might change with a new release.
The ExtensionLoader is responsible to load extensions to the OpenNLP library.
Exception indicates that an OpenNLP extension could not be loaded.
 
Interface for generating features for document categorization.
The FeatureGeneratorResourceProvider provides access to the resources available in the model.
Common evaluation parameters.
The FMeasure is a utility class for evaluators which measures precision, recall and the resulting f-measure.
Represents a labeler for nodes which contain traces so that these traces can be predicted by a Parser.
Encoder for head rules associated with parsing.
Allows repeated reads through a stream for certain model building types.
This exception indicates that the provided training data is insufficient to train a desired model.
Classes, fields, or methods annotated @Internal are for OpenNLP internal use only.
This exception indicates that a resource violates the expected data format.
Class for holding the document language and its confidence
Validates language codes against ISO 639 standards.
The interface for LanguageDetector which predicts the Language for a context.
A context generator interface for LanguageDetector.
A marker interface for evaluating language detectors.
A language model can calculate the probability p (between 0 and 1) of a certain sequence of tokens, given its underlying vocabulary.
 
Holds a classified document and its Language.
Represents a lemmatized sentence.
The common interface for lemmatizers.
Interface for the context generator used for probabilistic Lemmatizer.
A marker interface for evaluating lemmatizers.
A default, extended Span that holds additional information about a Span.
Interface for maximum entropy models.
Calculates the arithmetic mean of values added with the Mean.add(double) method.
A model type to pattern enumeration.
Enumeration of supported model types.
Interface that allows TagDictionary entries to be added and removed.
Interface for generating the context for a name finder by specifying a set of feature generators.
Encapsulates names for a single unit of text.
Reads objects from a stream.
 
 
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.
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.
 
Data structure for holding parse constituents.
Defines common methods for full-syntactic parsers.
A marker interface for evaluating parsers.
Enumeration of event types for a Parser.
Enumeration of supported Parser types.
Reads a plain text file and returns each line as a String object.
Interface for a BeamSearchContextGenerator used in POS tagging.
Represents an pos-tagged sentence.
The interface for part of speech taggers.
A marker interface for evaluating pos taggers.
This interface allows one to implement a prior distribution for use in maximum entropy model training.
A marker interface for classes with probabilistic capabilities.
This interface makes an Iterator resettable.
An iterator for a list which returns values in the opposite order as the typical list iterator.
Represents a generic type of processable elements.
Interface for SentenceDetector context generators.
The interface for sentence detectors, which find the sentence boundaries in a text.
 
A SentenceSample contains a document with begin indexes of the individual sentences.
 
An sentiment specific EvaluationMonitor to be used by the evaluator.
Class for holding text used for sentiment analysis.
Class which models a sequence.
Represents a weighted sequence of outcomes.
A classification model that can label an input Sequence.
A codec for sequences of type SequenceCodec.
Interface for streams of sequences used to train sequence models.
 
 
A marker interface so that implementing classes can refer to the corresponding ArtifactSerializer implementation.
Class for storing start and end integer offsets.
Reduces a word to its root form.
A factory that captures a stemmer configuration and mints configured Stemmer instances on demand.
Stop criteria for model training.
A pluggable filter that decides whether a token (or a sequence of tokens) is a stopword that should be removed during downstream text processing.
A marker-interface for a String interner implementation.
 
Interface to determine which tags are valid for a particular word based on a tag dictionary.
Exception to terminate the execution of a command line tool.
Classes, fields, or methods annotated @ThreadSafe are safe to use in multithreading contexts.
Interface for context generators required for tokenizer implementations.
The interface for tokenizers, which segment a string into its tokens.
A marker interface for evaluating tokenizers.
The interface for name finders which provide name tags for a sequence of tokens.
A marker interface for evaluating name finders.
A TokenSample is text with token spans.
 
Represents a common base for training implementations.
Configuration used for model training.
Enumeration of Training measures.
An interface to capture training progress of a model.
Common training parameters.
Reference data for Unicode dashes, plus O(1) membership lookups.
The Unicode general category of a dash code point.
One Unicode dash code point and its reference attributes.
Reference data for Unicode whitespace, plus O(1) membership lookups.
Line-breaking behavior, mirroring the "Notes" column of the reference table.
Unicode general category for a whitespace or related code point.
One related code point that is commonly confused with whitespace but is not (White_Space=no).
One Unicode whitespace code point and its reference attributes.
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.
A basic Tokenizer implementation which performs tokenization using white spaces.
A Tokenizer implementation which performs tokenization using word pieces.
A word vector.
A table that maps tokens to word vectors.