17.2021, Software: Natural Language Toolkit: NLTK-Lite Version 0.6.5
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LINGUIST List: Vol-17-2021. Tue Jul 11 2006. ISSN: 1068 - 4875.
Subject: 17.2021, Software: Natural Language Toolkit: NLTK-Lite Version 0.6.5
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1)
Date: 10-Jul-2006
From: Steven Bird < sb at csse.unimelb.edu.au >
Subject: Natural Language Toolkit: NLTK-Lite Version 0.6.5
-------------------------Message 1 ----------------------------------
Date: Tue, 11 Jul 2006 10:11:04
From: Steven Bird < sb at csse.unimelb.edu.au >
Subject: Natural Language Toolkit: NLTK-Lite Version 0.6.5
NLTK, the Natural Language Toolkit, is a suite of Python libraries and programs
for natural language processing. Version 0.6.5 has been released, and can be
downloaded from http://nltk.sourceforge.net/
CONTENTS
Software Modules: corpus readers, tokenizers & stemmers, taggers (regexp,
n-gram, backoff, Brill, HMM), parsers (recursive descent, shift-reduce, chart,
probabilistic, ...), clusterers (EM, k-means, ...), probability distributions,
chatbots, demonstrations, ...
Corpora and Corpus Samples: Brown Corpus, CMU Pronunciation Dictionary,
CoNNL-2000, Genesis, Gutenberg, IEER, Presidential Addresses, Names,
PP-Attachment, Senseval 2, TIMIT, Treebank, Words
Documentation: Tutorials and exercises (190pp), API documentation for all
software modules, installation instructions for Windows, Mac, Unix.
ChangeLog for Version 0.6.5 2006-07-09
* Code:
- improvements to shoebox module (Stuart Robinson, Greg Aumann)
- incorporated feature-based parsing into core NLTK-Lite
- corpus reader for Sinica treebank sample
- new stemmer package
* Contrib:
- hole semantics implementation (Peter Wang)
- Incorporating yaml
- new work on feature structures, unification, lambda calculus
- new work on shoebox package (Stuart Robinson, Greg Aumann)
* Corpora:
- Sinica treebank sample
* Tutorials:
- expanded discussion throughout, incl: left-recursion, trees, grammars,
feature-based grammar, agreement, unification, PCFGs,
baseline performance, exercises, improved display of trees
-Steven Bird
Linguistic Field(s): Cognitive Science
Computational Linguistics
Text/Corpus Linguistics
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