Paper: Automatic Construction Of Predicate-Argument Structure Patterns For Biomedical Information Extraction

ACL ID W06-1634
Title Automatic Construction Of Predicate-Argument Structure Patterns For Biomedical Information Extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006
Authors

This paper presents a method of automat- ically constructing information extraction patterns on predicate-argument structures (PASs) obtained by full parsing from a smaller training corpus. Because PASs represent generalized structures for syn- tactical variants, patterns on PASs are ex- pected to be more generalized than those on surface words. In addition, patterns are divided into components to improve recall and we introduce a Support Vector Machine to learn a prediction model using pattern matching results. In this paper, we present experimental results and analyze them on how well protein-protein interac- tions were extracted from MEDLINE ab- stracts. The results demonstrated that our method improved accuracy compared to a machine learning approach using surface word/part-of-speech p...