Enhancing Relation Extraction by Eliciting Selectional Constraint Features from Wikipedia

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.

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