KBUnify Babelfy


Knowledge base unification via sense embeddings and disambiguation
Powered by BabelNet BabelNet


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.

Reference Paper

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.

PaperBibtex entry


Claudio Delli Bovi

Claudio Delli Bovi
dellibovi [at] di.uniroma1 [dot] it
bn:17381128n @ BabelNetbn:17381128n

Luis Espinosa-Anke
luis [dot] espinosa [at] upf [dot] edu

Luis Espinosa-Anke

Roberto Navigli

Roberto Navigli
navigli [at] di.uniroma1 [dot] it
bn:09353187n @ BabelNetbn:09353187n


Unified Knowledge Base [ zip: 564 MB ]

Cross-Resource Alignments [ zip: 6.3 MB ]

Disambiguated Resources [ zip: 229 MB ]

Evaluation Data [ zip: 359 KB ]