Paper: A Feature-Enriched Tree Kernel for Relation Extraction

ACL ID P14-2011
Title A Feature-Enriched Tree Kernel for Relation Extraction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014

Tree kernel is an effective technique for rela- tion extraction. However, the traditional syn- tactic tree representation is often too coarse or ambiguous to accurately capture the semantic relation information between two entities. In this paper, we propose a new tree kernel, called feature-enriched tree kernel (FTK), which can enhance the traditional tree kernel by: 1) refining the syntactic tree representation by annotating each tree node with a set of dis- criminant features; and 2) proposing a new tree kernel which can better measure the syn- tactic tree similarity by taking all features into consideration. Experimental results show that our method can achieve a 5.4% F-measure im- provement over the traditional convolution tree kernel.