Natural Language Toolkit (NLTK) nltk.org
Authors: Steven Bird <stevenbird1@gmail.com>
Edward Loper <edloper@gmail.com>
Ewan Klein <ewan@inf.ed.ac.uk>
Copyright (C) 2001-2014 NLTK Project
For license information, see LICENSE.txt
NLTK -- the Natural Language Toolkit -- is a suite of open source
Python modules, data sets and tutorials supporting research and
development in Natural Language Processing.
Documentation: A substantial amount of documentation about how
to use NLTK, including a textbook and API documention, is
available from the NLTK website: http://nltk.org/
- The book covers a wide range of introductory topics in NLP, and
shows how to do all the processing tasks using the toolkit.
- The toolkit's reference documentation describes every module,
interface, class, method, function, and variable in the toolkit.
This documentation should be useful to both users and developers.
Mailing Lists: There are several mailing lists associated with NLTK:
- nltk: Public information and announcements about NLTK (very low volume)
http://groups.google.com/group/nltk
- nltk-users: Discussions amongst NLTK users
http://groups.google.com/group/nltk-users
- nltk-dev: Discussions amongst NLTK developers
http://groups.google.com/group/nltk-dev
- nltk-translation: Discussions about translating the NLTK book
http://groups.google.com/group/nltk-translation
- nltk-commits: Subversion commit logs for NLTK
http://groups.google.com/group/nltk-commits
Contributing: If you would like to contribute to NLTK,
please see http://nltk.org/contribute
Donating: Have you found the toolkit helpful? Please support NLTK development
by donating to the project via PayPal, using the link on the NLTK homepage.
Redistributing: NLTK source code is distributed under the Apache 2.0 License.
NLTK documentation is distributed under the Creative Commons
Attribution-Noncommercial-No Derivative Works 3.0 United States license.
NLTK corpora are provided under the terms given in the README file
for each corpus; all are redistributable, and available for non-commercial use.
NLTK may be freely redistributed, subject to the provisions of these licenses.
Citing: If you publish work that uses NLTK, please cite the NLTK book, as follows:
Bird, Steven, Edward Loper and Ewan Klein (2009).
Natural Language Processing with Python. O'Reilly Media Inc.
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nltk-3.0.0b1.zip
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txt:6个
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nltk-3.0.0b1.zip (309个子文件)
setup.cfg 59B
corpus.doctest 82KB
tree.doctest 38KB
featstruct.doctest 37KB
logic.doctest 33KB
parse.doctest 31KB
featgram.doctest 28KB
semantics.doctest 24KB
portuguese_en.doctest 22KB
wordnet.doctest 20KB
drt.doctest 19KB
inference.doctest 17KB
discourse.doctest 17KB
ccg.doctest 15KB
data.doctest 14KB
gluesemantics.doctest 12KB
collocations.doctest 11KB
chunk.doctest 11KB
toolbox.doctest 10KB
nonmonotonic.doctest 10KB
relextract.doctest 9KB
metrics.doctest 9KB
framenet.doctest 9KB
childes.doctest 9KB
chat80.doctest 8KB
probability.doctest 7KB
align.doctest 7KB
resolution.doctest 7KB
classify.doctest 7KB
propbank.doctest 7KB
treetransforms.doctest 5KB
tokenize.doctest 4KB
compat.doctest 4KB
internals.doctest 4KB
dependency.doctest 4KB
misc.doctest 3KB
grammartestsuites.doctest 3KB
index.doctest 3KB
gluesemantics_malt.doctest 2KB
simple.doctest 2KB
wsd.doctest 2KB
wordnet_lch.doctest 2KB
stem.doctest 2KB
bnc.doctest 2KB
generate.doctest 2KB
grammar.doctest 1KB
util.doctest 1KB
japanese.doctest 1KB
sentiwordnet.doctest 954B
tag.doctest 733B
MANIFEST.in 172B
not-zip-safe 1B
PKG-INFO 2KB
PKG-INFO 2KB
snowball.py 143KB
featstruct.py 100KB
downloader.py 89KB
util.py 85KB
chartparser_app.py 84KB
probability.py 81KB
framenet.py 80KB
wordnet.py 72KB
logic.py 66KB
tree.py 62KB
punkt.py 62KB
chart.py 60KB
maxent.py 58KB
chunkparser_app.py 54KB
regexp.py 53KB
grammar.py 52KB
data.py 51KB
drt.py 49KB
hmm.py 48KB
boxer.py 47KB
table.py 43KB
util.py 37KB
tree.py 36KB
rdparser_app.py 35KB
internals.py 34KB
wordnet_app.py 34KB
srparser_app.py 32KB
util.py 30KB
cfg.py 29KB
sequential.py 28KB
brill_trainer.py 27KB
glue.py 27KB
nonprojectivedependencyparser.py 26KB
chat80.py 25KB
resolution.py 25KB
tableau.py 25KB
recursivedescent.py 25KB
porter.py 24KB
concordance_app.py 23KB
projectivedependencyparser.py 23KB
evaluate.py 23KB
dependencygraph.py 23KB
text.py 22KB
featurechart.py 22KB
discourse.py 21KB
childes.py 21KB
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