Paper: Exploiting the Scope of Negations and Heterogeneous Features for Relation Extraction: A Case Study for Drug-Drug Interaction Extraction

ACL ID N13-1093
Title Exploiting the Scope of Negations and Heterogeneous Features for Relation Extraction: A Case Study for Drug-Drug Interaction Extraction
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

This paper presents an approach that exploits the scope of negation cues for relation extrac- tion (RE) without the need of using any specif- ically annotated dataset for building a separate negation scope detection classifier. New fea- tures are proposed which are used in two dif- ferent stages. These also include non-target entity specific features. The proposed RE ap- proach outperforms the previous state of the art for drug-drug interaction (DDI) extraction.