chatter: A library of simple NLP algorithms.

chatter is a collection of simple Natural Language Processing algorithms.

Chatter supports:

• Part of speech tagging with Averaged Perceptrons. Based on the Python implementation by Matthew Honnibal: (http://honnibal.wordpress.com/2013/09/11/a-good-part-of-speechpos-tagger-in-about-200-lines-of-python/) See NLP.POS for the details of part-of-speech tagging with chatter.

• Phrasal Chunking (also with an Averaged Perceptron) to identify arbitrary chunks based on training data.

• Document similarity; A cosine-based similarity measure, and TF-IDF calculations, are available in the NLP.Similarity.VectorSim module.

• Information Extraction patterns via (http://www.haskell.org/haskellwiki/Parsec/) Parsec

Chatter comes with models for POS tagging and Phrasal Chunking that have been trained on the Brown corpus (POS only) and the Conll2000 corpus (POS and Chunking)

Modules

[Last Documentation]

Downloads

• chatter-0.8.0.0.tar.gz [browse] (Cabal source package)
• Package description (as included in the package)

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Package maintainers

• RoganCreswick

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