Rooba
/
spaCy
mirror of https://github.com/explosion/spaCy.git
1
1
Fork 0
Code Issues Packages Projects Releases Wiki Activity
💫 Industrial-strength Natural Language Processing (NLP) in Python
2,414 Commits 70 Branches 177 Tags 298 MiB
Python 53.6%
MDX 31.4%
Cython 10.8%
JavaScript 2.6%
Sass 0.8%
Other 0.7%
Go to file
Matthew Honnibal d309622a27 * Add test for matcher end-point problem 2015-11-12 04:59:11 +11:00
appveyor@9f94a16f0e Adding submodule spaCy-appveyor-toolkit 2015-10-25 20:22:49 +03:00
bin * Train after parsing, not before. 2015-11-12 04:43:52 +11:00
contributors Add contributor. 2015-10-07 17:55:46 -07:00
corpora/en * Add wordnet 2015-09-21 19:06:48 +10:00
examples * Add simple deep feed-forward neural network text classification example. 2015-10-19 23:44:49 +11:00
lang_data * Fix non-breaking space in specials.json 2015-10-19 12:46:11 +11:00
services * Add displacy service 2015-10-28 17:36:11 +01:00
spacy * Add test for matcher end-point problem 2015-11-12 04:59:11 +11:00
website * Replace deprecated repvec reference in twitter-filter 2015-11-03 03:21:26 +11:00
.appveyor.yml Added project dir to PYTHONPATH 2015-10-25 21:51:33 +03:00
.gitignore Added Windows file to .gitignore 2015-10-13 10:58:30 +03:00
.gitmodules Switching to henningpeters/spaCy-appveyor-toolkit 2015-10-26 00:16:35 +03:00
.travis.yml * Roll back travis.yml testing models, due to memory restrictions 2015-11-09 03:05:01 +11:00
LICENSE.txt * Change from AGPL to MIT 2015-09-28 07:37:12 +10:00
MANIFEST.in * Add manifest file 2015-01-30 16:49:02 +11:00
README-MSVC.txt Small addition to MSVC readme 2015-10-25 23:05:11 +03:00
README.md Update README.md 2015-10-27 01:32:40 +11:00
bootstrap_python_env.sh * Add bootstrap script 2015-03-16 14:01:36 -04:00
fabfile.py * Fix prebuild command 2015-11-03 07:30:33 +01:00
requirements.txt * Fix requirements.txt 2015-11-06 17:35:59 +01:00
setup.py * Fix requirement of preshed 2015-11-08 18:09:21 +01:00
wordnet_license.txt * Add WordNet license file 2015-02-01 16:11:53 +11:00

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
  • OSX
  • Linux
  • Cygwin

Want to support:

  • Visual Studio

Difficult to support:

  • PyPy 2.7
  • PyPy 3.4