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Title: New Suite of Linguistically-Motivated NLP Tools
Submitter: Stephen Clark
Description: Version 1.0 of the C&C language processing tools is now freely
available for research use.

A feature of the tools is the combination of robust, efficient,
wide-coverage language processing with detailed linguistic output. We have
used the tools to analyse the entire Gigaword corpus (1 billion words) in
only 5 days using 18 processors. This speed of analysis, robustness and
wide coverage, combined with a high level of linguistic detail, represents
a breakthrough in Natural Language Processing (NLP) technology.

The tools comprise:

*Wide-coverage parser based on Combinatory Categorial Grammar. The parser
recovers labelled predicate-argument dependencies from CCG bank at over 85%
F-score, and from Depbank at over 81% F-score.

*The semantics tool Boxer which takes the output of the C&C parser and
taggers and produces output in the form of Discourse Representation Structures.

*A number of Maximum Entropy taggers: POS tagger, chunker, CCG
supertagger, and Named Entity Recognizer.

The tools are written in C++ (except Boxer, which is in Prolog) and have
been designed for large-scale NLP tasks which require sophisticated
linguistic processing.

The parser and taggers have been developed by James R. Curran and Stephen
Clark. Boxer has been developed by Johan Bos.

The tools, including source code, can be downloaded from:
Linguistic Field(s): Computational Linguistics

LL Issue: 18.1760
Date Posted: 10-Jun-2007

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