Towards event extraction from full texts on infectious diseases

Authors:
Sampo Pyysalo;Tomoko Ohta;Han-Cheol Cho;Dan Sullivan;Chunhong Mao;Bruno Sobral;Jun'ichi Tsujii;Sophia Ananiadou
Affiliations:
University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan;University of Tokyo, Tokyo, Japan;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia;Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia;University of Tokyo, Tokyo, Japan and University of Manchester, Manchester, UK;University of Manchester, Manchester, UK
Venue:
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Year:
2010

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Abstract

Event extraction approaches based on expressive structured representations of extracted information have been a significant focus of research in recent biomedical natural language processing studies. However, event extraction efforts have so far been limited to publication abstracts, with most studies further considering only the specific transcription factor-related subdo-main of molecular biology of the GENIA corpus. To establish the broader relevance of the event extraction approach and proposed methods, it is necessary to expand on these constraints. In this study, we propose an adaptation of the event extraction approach to a subdomain related to infectious diseases and present analysis and initial experiments on the feasibility of event extraction from domain full text publications.