PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Composite kernels for relation extraction
Frank Reichartz, Hannes Korte and Gerhard Paaß
Annual Meeting of the ACL archive Proceedings of the ACL-IJCNLP 2009 Conference pp. 365-368, 2009.

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.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Information Retrieval & Textual Information Access
ID Code:6768
Deposited By:Frank Reichartz
Deposited On:08 March 2010