Abstract
The automatic extraction of relations between entities expressed in natural language text is an important problem for IR and text understanding. In this paper we show how different kernels for parse trees can be combined to improve the relation extraction quality. On a public benchmark dataset the combination of a kernel for phrase grammar parse trees and for dependency parse trees outperforms all known tree kernel approaches alone suggesting that both types of trees contain complementary information for relation extraction. © 2009 ACL and AFNLP.
Cite
CITATION STYLE
Reichartz, F., Korte, H., & Paass, G. (2009). Composite kernels for relation extraction. In ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf. (pp. 365–368). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1667583.1667696
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