💫 Industrial-strength Natural Language Processing (NLP) in Python
Go to file
Matthew Honnibal 5897e74630 Merge pull request #200 from henningpeters/master
website improvements
2015-12-14 01:58:37 +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 * Fix sentence iteration bug in pos_tag example 2015-12-05 20:25:12 +01:00
lang_data * Fix lemma of let's, re Issue #177 2015-11-13 06:42:23 +11:00
services * Add displacy service 2015-10-28 17:36:11 +01:00
spacy change index server 2015-11-18 18:09:46 +01:00
website remove tutorials index page 2015-12-03 20:10:21 +01:00
.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 Python 3.5 is out 2015-11-25 08:58:05 +02:00
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 Add Python 3.5 2015-11-26 16:08:22 +02:00
bootstrap_python_env.sh * Add bootstrap script 2015-03-16 14:01:36 -04:00
fabfile.py remove tutorials index page 2015-12-03 20:10:21 +01:00
requirements.txt bump version 2015-11-21 19:04:57 +01:00
setup.py change github url to website 2015-12-03 20:17:13 +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
  • CPython 3.5
  • OSX
  • Linux
  • Cygwin

Want to support:

  • Visual Studio

Difficult to support:

  • PyPy 2.7
  • PyPy 3.4