Paper: A Shortest Path Dependency Kernel For Relation Extraction

ACL ID H05-1091
Title A Shortest Path Dependency Kernel For Relation Extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

We present a novel approach to relation extraction, based on the observation that the information required to assert a rela- tionship between two named entities in the same sentence is typically captured by the shortest path between the two en- tities in the dependency graph. Exper- iments on extracting top-level relations from the ACE (Automated Content Ex- traction) newspaper corpus show that the new shortest path dependency kernel out- performs a recent approach based on de- pendency tree kernels.