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48 lines
1.9 KiB
ReStructuredText
48 lines
1.9 KiB
ReStructuredText
.. spaCy documentation master file, created by
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sphinx-quickstart on Tue Aug 19 16:27:38 2014.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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spaCy NLP Tokenizer and Lexicon
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================================
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spaCy is a library for industrial strength NLP in Python and Cython. Its core
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values are efficiency, accuracy and minimalism.
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* Efficiency: spaCy is TODOx faster than the Stanford tools, and TODOx faster
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than NLTK. You won't find faster NLP tools. Using spaCy will save you
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thousands in server costs, and will force you to make fewer compromises.
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* Accuracy: All spaCy tools are within 0.5% of the current published
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state-of-the-art, on both news and web text. NLP moves fast, so always check
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the numbers --- and don't settle for tools that aren't backed by
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rigorous recent evaluation. An algorithm that was "close enough to state-of-the-art"
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5 years ago is probably crap by today's standards.
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* Minimalism: This isn't a library that covers 43 known algorithms to do X. You
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get 1 --- the best one --- with a simple, low-level interface. This keeps the
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code-base small and concrete. Our Python APIs use lists and
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dictionaries, and our C/Cython APIs use arrays and simple structs.
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Comparison
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----------
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+-------------+-------------+---+-----------+--------------+
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| POS taggers | Speed (w/s) | % Acc. (news) | % Acc. (web) |
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+-------------+-------------+---------------+--------------+
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| spaCy | | | |
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+-------------+-------------+---------------+--------------+
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| Stanford | 16,000 | | |
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+-------------+-------------+---------------+--------------+
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| NLTK | | | |
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+-------------+-------------+---------------+--------------+
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.. toctree::
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:hidden:
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:maxdepth: 3
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what/index.rst
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why/index.rst
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how/index.rst
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