KB-Unify is an approach for integrating the output of different Open Information Extraction systems into a single unified and fully disambiguated knowledge repository. The unification algorithm consists of three main steps: (1) disambiguation of relation argument pairs via a sense-based 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.
Claudio Delli Bovi, Luis Espinosa-Anke and Roberto Navigli.
Knowledge Base Unification via Sense Embeddings and Disambiguation. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 726–736, Lisbon, Portugal, 17-21 September 2015.
luis [dot] espinosa [at] upf [dot] edu
KB-Unify is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.
Last update: Oct 22nd 2016 by Claudio Delli Bovi