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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Matthew Honnibal e4263a241a * Tests passing for reorganized version
2014-07-07 04:23:46 +02:00
data/en * Reorganized, moving language-independent stuff to spacy. The functions in spacy ask for the dictionaries and split function on input, but the language-specific modules are curried versions that use the globals 2014-07-07 04:21:06 +02:00
docs * Add initial docs stuff 2014-07-05 20:49:46 +02:00
ext * Add ext stuff, while I figure out how to get it working as a different project 2014-07-05 20:51:04 +02:00
include * Add ext stuff, while I figure out how to get it working as a different project 2014-07-05 20:51:04 +02:00
spacy * Reorganized, moving language-independent stuff to spacy. The functions in spacy ask for the dictionaries and split function on input, but the language-specific modules are curried versions that use the globals 2014-07-07 04:21:06 +02:00
tests * Tests passing for reorganized version 2014-07-07 04:23:46 +02:00
.gitignore * Add gitignore 2014-07-05 20:50:01 +02:00
fabfile.py * Add build/setup stuff 2014-07-05 20:49:34 +02:00
README.md Initial commit 2014-07-04 01:15:40 +10:00
requirements.txt * Add build/setup stuff 2014-07-05 20:49:34 +02:00
setup.py * Add build/setup stuff 2014-07-05 20:49:34 +02:00

README.md

spaCy

Lightning fast, full-cream NL tokenization. Tokens are pointers to rich Lexeme structs.