Syntactic Tree-based Relation Extraction Using a Generalization of Collins and Duffy Convolution Tree Kernel

Relation extraction is a challenging task in natural language processing. Syntactic features are recently shown to be quite effective for relation extraction. In this paper, we generalize the state of the art syntactic convolution tree kernel introduced by Collins and Duffy. The proposed generalized kernel is more flexible and customizable, and can be conveniently utilized for systematic generation of more effective application specific syntactic sub-kernels. Using the generalized kernel, we will also propose a number of novel syntactic sub-kernels for relation extraction. These kernels show a remarkable performance improvement over the original Collins and Duffy kernel in the extraction of ACE-2005 relation types.