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spaCy
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💫 Industrial-strength Natural Language Processing (NLP) in Python
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Matthew Honnibal 96b835a3d4 * Upd for refactored Tokens class. Now gets 95.74, 185ms training on swbd_wsj_ewtb, eval on onto_web, Google POS tags. 2014-10-23 03:20:02 +11:00
data * Add file for infix patterns 2014-10-14 20:26:43 +11:00
docs * Update docs 2014-10-15 21:50:34 +11:00
spacy * Upd for refactored Tokens class. Now gets 95.74, 185ms training on swbd_wsj_ewtb, eval on onto_web, Google POS tags. 2014-10-23 03:20:02 +11:00
tests * Add test for reading in POS tags 2014-10-22 10:18:43 +11:00
.gitignore * Upd gitignore 2014-08-20 17:04:33 +02:00
README.md Initial commit 2014-07-04 01:15:40 +10:00
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
requirements.txt * Rename external hashing lib, from trustyc to preshed 2014-09-26 18:40:03 +02:00
setup.py * Add greedy pos tagger 2014-10-22 10:17:26 +11:00

README.md

spaCy

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