Supervised distributional hypernym discovery via domain adaptation

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• dc.contributor.author Espinosa-Anke, Luisca
• dc.contributor.author Camacho-Collados, Joseca
• dc.contributor.author Delli Bovi, Claudioca
• dc.contributor.author Saggion, Horacioca
• dc.date.accessioned 2018-01-22T10:38:00Z
• dc.date.available 2018-01-22T10:38:00Z
• dc.date.issued 2016
• dc.description Comunicació presentada a la Conference on Empirical Methods in Natural Language Processing celebrada els dies 1 a 5 de novembre de 2016 a Austin, Texas.
• dc.description.abstract Lexical taxonomies are graph-like hierarchical structures that provide a formal representation of knowledge. Most knowledge graphs to date rely on is-a (hypernymic) relations as the backbone of their semantic structure. In this paper, we propose a supervised distributional framework for hypernym discovery which operates at the sense level, enabling large-scale automatic acquisition of disambiguated taxonomies. By exploiting semantic regularities between hyponyms and hypernyms in embeddings spaces, and integrating a domain clustering algorithm, our model becomes sensitive to the target data. We evaluate several configurations of our approach, training with information derived from a manually created knowledge base, along with hypernymic relations obtained from Open Information Extraction systems. The integration of both sources of knowledge yields the best overall results according to both automatic and manual evaluation on ten different domains.en
• dc.description.sponsorship This work is partially funded by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and under the TUNER project (TIN2015-65308-C5-5-R, MINECO/FEDER, UE). The authors also acknowledge support from Dr. Inventor (FP7-ICT-2013.8.1611383). José CamachoCollados is supported by a Google Doctoral Fellowship in Natural Language Processing.
• dc.format.mimetype application/pdfca
• dc.identifier.citation Espinosa-Anke L, Camacho-Collados J, Delli Bovi C, Saggion H. Supervised distributional hypernym discovery via domain adaptation. In: Conference on Empirical Methods in Natural Language Processing; 2016 Nov 1-5; Austin, TX. Red Hook (NY): ACL; 2016. p. 424-35.
• dc.identifier.uri http://hdl.handle.net/10230/33714
• dc.language.iso eng
• dc.publisher ACL (Association for Computational Linguistics)ca
• dc.relation.ispartof Conference on Empirical Methods in Natural Language Processing; 2016 Nov 1-5; Austin, TX. Red Hook (NY): ACL; 2016. p. 424-35.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/611383
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-65308-C5-5-R
• dc.rights © ACL, Creative Commons Attribution 4.0 License
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.other Semàntica
• dc.title Supervised distributional hypernym discovery via domain adaptationca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion