[![Travis CI status](https://travis-ci.org/spacy-io/spaCy.svg?branch=master)](https://travis-ci.org/spacy-io/spaCy) spaCy: Industrial-strength NLP ============================== spaCy is a library for advanced natural language processing in Python and Cython. Documentation and details: https://spacy.io/ spaCy is built on the very latest research, but it isn't researchware. It was designed from day 1 to be used in real products. It's commercial open-source software, released under the MIT license. Features -------- * Labelled dependency parsing (91.8% accuracy on OntoNotes 5) * Named entity recognition (82.6% accuracy on OntoNotes 5) * Part-of-speech tagging (97.1% accuracy on OntoNotes 5) * Easy to use word vectors * All strings mapped to integer IDs * Export to numpy data arrays * Alignment maintained to original string, ensuring easy mark up calculation * Range of easy-to-use orthographic features. * No pre-processing required. spaCy takes raw text as input, warts and newlines and all. Top Peformance ------------- * Fastest in the world: <50ms per document. No faster system has ever been announced. * Accuracy within 1% of the current state of the art on all tasks performed (parsing, named entity recognition, part-of-speech tagging). The only more accurate systems are an order of magnitude slower or more. Supports -------- * CPython 2.7 * CPython 3.4 * CPython 3.5 * OSX * Linux * Windows (Cygwin, MinGW, Visual Studio) Difficult to support: * PyPy 2.7 * PyPy 3.4