Apache OpenNLP
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports common NLP tasks such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution.
APIs
Apache OpenNLP
OpenNLP provides a Java API for NLP tasks including tokenization, sentence detection, POS tagging, named entity recognition, chunking, parsing, and language detection, with supp...
Capabilities
Apache OpenNLP NLP Pipeline Workflow
End-to-end NLP processing workflow combining language detection, sentence detection, tokenization, POS tagging, NER, chunking, and parsing for comprehensive text analysis.
Run with NaftikoFeatures
Detects document language using ISO-639-3 classification
Splits text into individual sentences with character offsets
Segments text into words and punctuation with position tracking
Detects persons, locations, organizations, and other named entities
Assigns Penn Treebank POS tags to each token
Reduces tokens to their dictionary base forms
Identifies noun phrases, verb phrases, and other syntactic chunks
Builds full syntactic parse trees using constituency parsing
Classifies documents into predefined categories
Train custom models with Maxent, Perceptron, or Naive Bayes algorithms
Use Cases
Extract structured data from unstructured text documents
Automatically categorize documents by topic or sentiment
Improve search relevance with NLP-based query processing
Analyze large text corpora for entities, topics, and patterns
Build conversational AI with NLP intent and entity extraction
Integrations
Integrate OpenNLP with Apache Solr for NLP-enhanced search
Use OpenNLP analyzers in Lucene text processing pipelines
Real-time NLP processing with Apache Flink data streams
Apache UIMA framework integration for unstructured information analysis
Available on Maven Central for Java build system integration