explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2026-01-21 07:44:32 +03:00
Code Issues Packages Projects Releases Wiki Activity
💫 Industrial-strength Natural Language Processing (NLP) in Python
1,880 Commits 75 Branches 184 Tags 268 MiB
Python 54.1%
MDX 31.2%
Cython 10.5%
JavaScript 2.6%
Sass 0.8%
Other 0.7%
a1292adb82
Go to file
Matthew Honnibal a1292adb82 * Test new text and text_with_ws attributes in Token
2015-09-13 10:30:37 +10:00
bin
contributors Merge pull request #85 from NSchrading/master 2015-09-07 09:05:19 +10:00
corpora/en
examples * Begin rewriting twitter_filter examples 2015-08-22 22:12:26 +02:00
lang_data
spacy * Remove assertion from vocab.pyx 2015-09-13 10:30:08 +10:00
tests * Test new text and text_with_ws attributes in Token 2015-09-13 10:30:37 +10:00
.gitignore
.travis.yml
bootstrap_python_env.sh * Add bootstrap script 2015-03-16 14:01:36 -04:00
dev_setup.py
fabfile.py
LICENSE.txt
MANIFEST.in
README.md
requirements.txt * Require preshed 0.41 2015-07-25 22:36:43 +02:00
setup.py * Inc version 2015-09-13 01:26:29 +02:00
wordnet_license.txt

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. You can buy a commercial license, or you can use it under the AGPL.

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 Pefomance

  • 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