mirror of https://github.com/explosion/spaCy.git
aiartificial-intelligencecythondata-sciencedeep-learningentity-linkingmachine-learningnamed-entity-recognitionnatural-language-processingneural-networkneural-networksnlpnlp-librarypythonspacystarred-explosion-repostarred-repotext-classificationtokenization
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README.md
spaCy: Industrial-strength NLP
spaCy is a library for advanced natural language processing in Python and Cython.
Documentation and details: http://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
- OSX
- Linux
- Cygwin
Want to support:
- Visual Studio
Difficult to support:
- PyPy 2.7
- PyPy 3.4