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* Add benchmark details.

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Matthew Honnibal 2015-01-25 01:25:27 +11:00
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docs/source/index.rst
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@ -216,10 +216,19 @@ spaCy gives you easy and efficient access to them, which lets you build all
sorts of use products and features that were previously impossible.
Efficiency
----------
Speed Comparison
----------------
.. table:: Efficiency comparison. See `Benchmarks`_ for details.
**Set up**: 100,000 plain-text documents were streamed from an SQLite3
database, and processed with an NLP library, to one of three levels of detail
--- tokenization, tagging, or parsing. The tasks are additive: to parse the
text you have to tokenize and tag it. The pre-processing was not subtracted
from the times --- I report the time required for the pipeline to complete.
I report mean times per document, in milliseconds.
**Hardware**: Intel i7-3770 (2012)
.. table:: Efficiency comparison. Lower is better.
+--------------+---------------------------+--------------------------------+
| | Absolute (ms per doc) | Relative (to spaCy) |
@ -266,8 +275,8 @@ representations.
It's evaluated against the current best published systems, following the standard
methodologies. These evaluations show that it performs extremely well.
Accuracy
--------
Accuracy Comparison
-------------------
.. table:: Accuracy comparison, on the standard benchmark data from the Wall Street Journal.