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Título:	Knowledge base unification via sense embeddings and disambiguation
Autor/a:	Delli Bovi, Claudio; Espinosa-Anke, Luis; Navigli, Roberto
Abstract:	Paper presented at The 2015 Conference on Empirical Methods in Natural Language; 2015 Sept 17-21; Lisbon, Portugal.
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.
Abstract:	The authors gratefully acknowledge the support of the ERC Starting Grant MultiJEDI No. 259234.
Derechos:	© ACL, Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License https://creativecommons.org/licenses/by-nc-sa/3.0/
Tipo de documento:	Objeto de conferencia Artículo - Versión publicada
Editor:	ACL (Association for Computational Linguistics)
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