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EXTRACTING SECONDARY BIO‐EVENT ARGUMENTS WITH EXTRACTION CONSTRAINTS
Author(s) -
Sasaki Yutaka,
Wang Xinglong,
Ananiadou Sophia
Publication year - 2011
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.2011.00406.x
Subject(s) - crfs , computer science , conditional random field , task (project management) , event (particle physics) , natural language processing , parsing , biomedical text mining , artificial intelligence , focus (optics) , information extraction , question answering , text mining , physics , quantum mechanics , management , optics , economics
This paper describes our bio‐event extraction system developed for the BioNLP 2009 Shared Task 2, with focus on its capability of extracting secondary biological event arguments from literature. Shared Task 2 is particularly interesting because when browsing literature, biologists often need to understand conditions surrounding biological events, which are usually expressed by secondary event arguments (e.g., binding sites). To achieve our goal, we take an approach that extracts n ‐ary relations from text using event extraction constraints automatically generated from a training corpus. Event constraints consist of sequences of trigger words and semantic roles which we automatically identify using Conditional Random Fields (CRFs). Unlike most other systems participating in this shared task, our system is light‐weight and relies on neither external resources (e.g., Ontologies and dictionaries) nor natural language processing software (e.g., POS taggers and parsers). The official test results show that our approach performed well on extracting secondary arguments in Task 2, yielding the highest precision at 76.62% and the second highest F‐measure at 43.22%.