UTurku: Drug Named Entity Recognition and Drug-Drug Interaction Extraction Using SVM Classification and Domain Knowledge

Abstract

The DDIExtraction 2013 task in the SemEval conference concerns the detection of drug names and statements of drug-drug interactions (DDI) from text. Extraction of DDIs is important for providing up-to-date knowledge on adverse interactions between coadministered drugs. We apply the machine learning based Turku Event Extraction System to both tasks. We evaluate three feature sets, syntactic features derived from deep parsing, enhanced optionally with features derived from DrugBank or from both DrugBank and MetaMap. TEES achieves F-scores of 60 % for the drug name recognition task and 59 % for the DDI extraction task. 1