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Visual Studio Express Community 2015 running on Windows Server 2012 Standard: https://ci.spacy.io/builders/win64-0/builds/38/steps/shell_1/logs/stdio
57 lines
1.6 KiB
Markdown
57 lines
1.6 KiB
Markdown
[![Travis CI status](https://travis-ci.org/honnibal/spaCy.svg?branch=master)](https://travis-ci.org/honnibal/spaCy)
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[![Appveyor status](https://ci.appveyor.com/api/projects/status/395x7jn0rakfs4ti/branch/master?svg=true)](https://ci.appveyor.com/project/honnibal/spacy/branch/master)
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spaCy: Industrial-strength NLP
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==============================
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spaCy is a library for advanced natural language processing in Python and Cython.
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Documentation and details: http://spacy.io/
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spaCy is built on the very latest research, but it isn't researchware. It was
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designed from day 1 to be used in real products. It's commercial open-source
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software, released under the MIT license.
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Features
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--------
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* Labelled dependency parsing (91.8% accuracy on OntoNotes 5)
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* Named entity recognition (82.6% accuracy on OntoNotes 5)
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* Part-of-speech tagging (97.1% accuracy on OntoNotes 5)
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* Easy to use word vectors
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* All strings mapped to integer IDs
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* Export to numpy data arrays
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* Alignment maintained to original string, ensuring easy mark up calculation
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* Range of easy-to-use orthographic features.
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* No pre-processing required. spaCy takes raw text as input, warts and newlines and all.
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Top Peformance
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-------------
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* Fastest in the world: <50ms per document. No faster system has ever been
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announced.
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* Accuracy within 1% of the current state of the art on all tasks performed
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(parsing, named entity recognition, part-of-speech tagging). The only more
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accurate systems are an order of magnitude slower or more.
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Supports
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--------
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* CPython 2.7
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* CPython 3.4
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* CPython 3.5
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* OSX
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* Linux
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* Cygwin
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* Visual Studio
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Difficult to support:
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* PyPy 2.7
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* PyPy 3.4
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