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💫 Industrial-strength Natural Language Processing (NLP) in Python
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0152831c89
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Matthew Honnibal 0152831c89 * Refactor tokenization, enable cache, and ensure we look up specials correctly even when there's confusing punctuation surrounding the token.
2014-09-16 18:01:46 +02:00
data * Refactor tokenization, splitting it into a clearer life-cycle. 2014-09-16 13:16:02 +02:00
docs * Tweak overview docs 2014-09-07 21:29:41 +02:00
spacy * Refactor tokenization, enable cache, and ensure we look up specials correctly even when there's confusing punctuation surrounding the token. 2014-09-16 18:01:46 +02:00
tests * Refactor tokenization, enable cache, and ensure we look up specials correctly even when there's confusing punctuation surrounding the token. 2014-09-16 18:01:46 +02:00
.gitignore * Upd gitignore 2014-08-20 17:04:33 +02:00
fabfile.py * Only store LexemeC structs in the vocabulary, transforming them to Lexeme objects for output. Moving away from Lexeme objects for Tokens soon. 2014-09-11 12:28:38 +02:00
README.md Initial commit 2014-07-04 01:15:40 +10:00
requirements.txt * Temporarily remove sparsehash requirement 2014-08-20 17:12:19 +02:00
setup.py * PointerHash working, efficiency is good. 6-7 mins 2014-09-13 16:43:59 +02:00

README.md

spaCy

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