Three BioNLP tools powered by a biological lexicon

Authors:
Yutaka Sasaki;Paul Thompson;John McNaught;Sophia Ananiadou
Affiliations:
University of Manchester;University of Manchester;University of Manchester and National Centre for Text Mining, Manchester, United Kingdom;University of Manchester and National Centre for Text Mining, Manchester, United Kingdom
Venue:
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session
Year:
2009

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ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning

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Abstract

In this paper, we demonstrate three NLP applications of the BioLexicon, which is a lexical resource tailored to the biology domain. The applications consist of a dictionary-based POS tagger, a syntactic parser, and query processing for biomedical information retrieval. Biological terminology is a major barrier to the accurate processing of literature within biology domain. In order to address this problem, we have constructed the BioLexicon using both manual and semiautomatic methods. We demonstrate the utility of the biology-oriented lexicon within three separate NLP applications.