We propose an approach for extracting relations between entities from biomedical literature based solely on shallow linguistic information. We use a combination of kernel functions to integrate two different information sources: (i) the whole sentence where the relation appears, and (ii) the local contexts around the interacting entities. We performed experiments on extracting gene and protein interactions from two different data sets. The results show that our approach outperforms most of the previous methods based on syntactic and semantic information.
Giuliano et al. REF proposed in 2006 a kernel based only on shallow linguistic information of the sentences.
Exploiting Shallow Linguistic Information For Relation Extraction From Biomedical Literature
Conference Of The European Association For Computational Linguistics
Computer Science