A Shortest Path Dependency Kernel for Relation Extraction
Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, page 724--731. Vancouver, British Columbia, Canada, Association for Computational Linguistics, (October 2005)Abstract
We present a novel approach to relation extraction, based on the observation that the information required to assert a relationship between two named entities in the same sentence is typically captured by the shortest path between the two entities in the dependency graph. Experiments on extracting top-level relations from the ACE (Automated Content Extraction) newspaper corpus show that the new shortest path dependency kernel outperforms a recent approach based on dependency tree kernels.
