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Apache OpenNLP A Machine Learning Toolkit for Natural Language Processing

What is Apache OpenNLP?

The Apache OpenNLP library is a machine learning based toolkit designed for the processing of natural language text. It provides support for a wide array of common NLP tasks.

Such tasks supported by OpenNLP, include sentence segmentation, tokenization, lemmatization, part-of-speech tagging, named entity extraction, chunking, parsing, language detection, and coreference resolution. The library is designed to be readily integrated into various applications requiring robust natural language processing capabilities.

Features

  • Sentence Segmentation: Detects sentence boundaries in text.
  • Tokenization: Splits text into individual tokens (words, punctuation, etc.).
  • Lemmatization: Determines the base or dictionary form of words.
  • Part-of-Speech Tagging: Assigns part-of-speech tags (noun, verb, adjective, etc.) to words.
  • Named Entity Extraction: Identifies and classifies named entities (person, organization, location, etc.).
  • Chunking: Groups words into phrases based on syntactic structure.
  • Parsing: Analyzes the grammatical structure of sentences.
  • Language Detection: Identifies the language of a given text.
  • Coreference Resolution: Determines which words refer to the same entities in a text.

Use Cases

  • Text analysis
  • Natural language understanding
  • Building custom NLP pipelines
  • Integrating NLP capabilities into applications

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