NLP4J – NLP framework for JVM languages

The Natural Language Processing for JVM languages (NLP4J) project provides:

• NLP tools readily available for research in various disciplines.
• Frameworks for fast development of efficient and robust NLP components.
• API for manipulating computational structures in NLP (e.g., dependency graph).

Features include:

• Tokenization – takes a raw text and splits tokens by their morphological aspects. It also groups tokens into sentences. The tokenizer is based on the LDC tokenizer used for creating English Treebanks although it uses more robust heuristics:
  • Emoticons are recognized as one unit (e.g., :-), ^_^).
  • Hyperlinks are recognized as one unit (emory.edu, jinho@emory.edu, index.html).
  • Numbers consisting of punctuation are recognized as one unit (e.g., 0.1, 2/3).
  • Repeated punctuation are grouped together (e.g., ---, ...).
  • Abbreviations are recognized as one unit (e.g., Prof., Ph.D).
  • File extensions are not tokenized (e.g., clearnlp.zip, tokenizer.doc).
  • Units are tokenized (e.g., 1 kg, 2 cm).
  • Usernames including periods are recognized as one unit (e.g., jinho.choi).
• Morphological analyzer – enerates root forms (lemmas) of word tokens. It is a rule-based analyzer inspired by the WordNet morphy although it uses a larger dictionary gathered from various sources and more advanced heuristics. It also normalizes numbers, redundant punctuation, hyperlinks, etc.
• Part-of-Speech Tagging – uses the generalized model from dynamic model selection and utilizes ambiguity classes trained on a large corpus.
• Named Entity Recognition – uses both sparse and dense features extracted from named entity gazetteers, word clusters, and word embeddings.
• Dependency Parsing – uses a transition-based, non-projective parsing algorithm showing a linear-time speed for both projective and non-projective parsing.

Website: emorynlp.github.io/nlp4j
Support: Forum, GitHub Code Repository
Developer: Emory NLP research group
License: Apache License, Version 2.0

NLP4J is written in Java. Learn Java with our recommended free books and free tutorials.

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