论文信息 - BioEve: Bio-Molecular Event Extraction from Text Using Semantic Classification and Dependency Parsing

BioEve: Bio-Molecular Event Extraction from Text Using Semantic Classification and Dependency Parsing

In this paper, we present BioEve a fully automated event extraction system for bio-medical text. It first semantically classifies each sentence to the class type of the event mentioned in the sentence, and then using high coverage hand-crafted rules, it extracts the participants of that event. We participated in Task 1 of BioNLP 2009 Shared task, and the final evaluation results are described here. Our experimentation with different approaches to classify a sentence to bio-interaction classes are also shared.

[1] Alfonso Valencia,et al. The Frame-Based Module of the SUISEKI Information Extraction System , 2002, IEEE Intell. Syst..

[2] T. Takagi,et al. Toward information extraction: identifying protein names from biological papers. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[3] Yuka Tateisi,et al. Annotation of Predicate-argument Structure on Molecular Biology Text , 2004 .

[4] Miguel A. Andrade-Navarro,et al. Automatic Extraction of Biological Information from Scientific Text: Protein-Protein Interactions , 1999, ISMB.

[5] Ralf Zimmer,et al. RelEx - Relation extraction using dependency parse trees , 2007, Bioinform..

[6] Jun'ichi Tsujii,et al. Event Extraction from Biomedical Papers Using a Full Parser , 2000, Pacific Symposium on Biocomputing.

[7] Toshihisa Takagi,et al. Automated extraction of information on protein-protein interactions from the biological literature , 2001, Bioinform..