University of Turku in the BioNLP'11 Shared Task

BMC Bioinformatics

Proceedings

Jari Björne¹  Tapio Salakoski¹  Filip Ginter¹ 

[1] Department of Information Technology, University of Turku, Turku Centre for Computer Science (TUCS), Joukahaisenkatu 3-5, 20520, Turku, Finland;

关键词: Share Task;    Event Extraction;    Event Argument;    Coreference Resolution;    Trigger Detection;   

DOI  :  10.1186/1471-2105-13-S11-S4

来源: Springer

【 摘 要 】

BackgroundWe present a system for extracting biomedical events (detailed descriptions of biomolecular interactions) from research articles, developed for the BioNLP'11 Shared Task. Our goal is to develop a system easily adaptable to different event schemes, following the theme of the BioNLP'11 Shared Task: generalization, the extension of event extraction to varied biomedical domains. Our system extends our BioNLP'09 Shared Task winning Turku Event Extraction System, which uses support vector machines to first detect event-defining words, followed by detection of their relationships.ResultsOur current system successfully predicts events for every domain case introduced in the BioNLP'11 Shared Task, being the only system to participate in all eight tasks and all of their subtasks, with best performance in four tasks. Following the Shared Task, we improve the system on the Infectious Diseases task from 42.57% to 53.87% F-score, bringing performance into line with the similar GENIA Event Extraction and Epigenetics and Post-translational Modifications tasks. We evaluate the machine learning performance of the system by calculating learning curves for all tasks, detecting areas where additional annotated data could be used to improve performance. Finally, we evaluate the use of system output on external articles as additional training data in a form of self-training.ConclusionsWe show that the updated Turku Event Extraction System can easily be adapted to all presently available event extraction targets, with competitive performance in most tasks. The scope of the performance gains between the 2009 and 2011 BioNLP Shared Tasks indicates event extraction is still a new field requiring more work. We provide several analyses of event extraction methods and performance, highlighting potential future directions for continued development.

【 授权许可】

CC BY   
© Björne et al; licensee BioMed Central Ltd. 2012