Knowledge base unification via sense embeddings and disambiguation

Delli Bovi, Claudio; Espinosa-Anke, Luis; Navigli, Roberto

Knowledge base unification via sense embeddings and disambiguation

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Citation

Delli Bovi C, Espinosa-Anke L, Navigli R. Knowledge base unification via sense embeddings and disambiguation. In: The 2015 Conference on Empirical Methods in Natural Language; 2015 Sept 17-21; Lisbon, Portugal. [Stroudsburg]: ACL (Association for Computational Linguistics); 2015. p.726-36.

Abstract

We present KB-UNIFY, a novel approach for integrating the output of different Open Information Extraction systems into a single unified and fully disambiguated knowledge repository. KB-UNIFY consists of three main steps: (1) disambiguation of relation argument pairs via a sensebased vector representation and a large unified sense inventory; (2) ranking of semantic relations according to their degree of specificity; (3) cross-resource relation alignment and merging based on the semantic similarity of domains and ranges. We tested KB-UNIFY on a set of four heterogeneous knowledge bases, obtaining high-quality results. We discuss and provide evaluations at each stage, and release output and evaluation data for the use and scrutiny of the community.