Enhancing relation extraction by eliciting selectional constraint features from wikipedia

  • Authors:

  • Gang Wang;Huajie Zhang;Haofen Wang;Yong Yu

  • Affiliations:

  • Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China

  • Venue:
  • NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
  • Year:
  • 2007

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Abstract

Selectional Constraints are usually checked for detecting semantic relations. Previous work usually defined the constraints manually based on handcrafted concept taxonomy, which is time-consuming and impractical for large scale relation extraction. Further, the determination of entity type (e.g. NER) based on the taxonomy cannot achieve sufficiently high accuracy. In this paper, we propose a novel approach to extracting relation instances using the features elicited from Wikipedia, a free online encyclopedia. The features are represented as selectional constraints and further employed to enhance the extraction of relations. We conduct case studies on the validation of the extracted instances for two common relations hasArtist(album, artist) and hasDirector(film, director). Substantially high extraction precision (around 0.95) and validation accuracy (near 0.90) are obtained.