chatter-0.5.2.0: 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
POSfor 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
VectorSimmodule. - 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
- Data
- NLP
- Corpora
- ML
- NLP.POS Part-of-Speech tagging facilities.
- Similarity
- NLP.Tokenize
- NLP.Types