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. © 2005 Association for Computational Linguistics.
Cite
CITATION STYLE
Bunescu, R. C., & Mooney, R. J. (2005). A shortest path dependency kernel for relation extraction. In HLT/EMNLP 2005 - Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 724–731). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220575.1220666
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