spaCy/docs/source/index.rst
2014-11-04 17:01:54 +11:00

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.. spaCy documentation master file, created by
sphinx-quickstart on Tue Aug 19 16:27:38 2014.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
spaCy NLP Tokenizer and Lexicon
================================
spaCy is a library for industrial strength NLP in Python. Its core
values are:
* **Efficiency**: You won't find faster NLP tools. For shallow analysis, it's 10x
faster than Stanford Core NLP, and over 200x faster than NLTK. Its parser is
over 100x faster than Stanford's.
* **Accuracy**: All spaCy tools are within 0.5% of the current published
state-of-the-art, on both news and web text. NLP moves fast, so always check
the numbers --- and don't settle for tools that aren't backed by
rigorous recent evaluation.
* **Minimalism**: This isn't a library that covers 43 known algorithms to do X. You
get 1 --- the best one --- with a simple, low-level interface. This keeps the
code-base small and concrete. Our Python APIs use lists and
dictionaries, and our C/Cython APIs use arrays and simple structs.
Comparison
----------
+----------------+-------------+--------+---------------+--------------+
| Tokenize & Tag | Speed (w/s) | Memory | % Acc. (news) | % Acc. (web) |
+----------------+-------------+--------+---------------+--------------+
| spaCy | 107,000 | 1.3gb | 96.7 | |
+----------------+-------------+--------+---------------+--------------+
| Stanford | 8,000 | 1.5gb | 96.7 | |
+----------------+-------------+--------+---------------+--------------+
| NLTK | 543 | 61mb | 94.0 | |
+----------------+-------------+--------+---------------+--------------+
.. toctree::
:hidden:
:maxdepth: 3
what/index.rst
why/index.rst
how/index.rst