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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Henning Peters f3e73c4ca4 spaCy now passes all tests for visual studio 
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
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README.md

Travis CI status Appveyor status

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
  • CPython 3.5
  • OSX
  • Linux
  • Cygwin
  • Visual Studio

Difficult to support:

  • PyPy 2.7
  • PyPy 3.4