Paper: Unsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web

ACL ID P09-1115
Title Unsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper presents an unsupervised rela- tion extraction method for discovering and enhancing relations in which a specified concept in Wikipedia participates. Using respective characteristics of Wikipedia ar- ticles and Web corpus, we develop a clus- tering approach based on combinations of patterns: dependency patterns from depen- dency analysis of texts in Wikipedia, and surface patterns generated from highly re- dundant information related to the Web. Evaluations of the proposed approach on two different domains demonstrate the su- periority of the pattern combination over existing approaches. Fundamentally, our method demonstrates how deep linguistic patterns contribute complementarily with Web surface patterns to the generation of various relations.