Distributed prediction of relations for entities: the Easy, the Difficult, and the impossible

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• dc.contributor.author Boleda, Gemmaca
• dc.contributor.author Gupta, Abhijeetca
• dc.contributor.author Padó, Sebastianca
• dc.date.accessioned 2018-09-28T07:42:00Z
• dc.date.available 2018-09-28T07:42:00Z
• dc.date.issued 2017
• dc.description Comunicació presentada a la 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), celebrat els dies 3 i 4 d'agost de 2017 a Vancouver, Canada.
• dc.description.abstract Word embeddings are supposed to provide easy access to semantic relations such as “male of” (man–woman). While this claim has been investigated for concepts, little is known about the distributional behavior of relations of (Named) Entities. We describe two word embedding-based models that predict values for relational attributes of entities, and analyse them. The task is challenging, with major performance differences between relations. Contrary to many NLP tasks, high difficulty for a relation does not result from low frequency, but from (a) one-to-many mappings; and (b) lack of context patterns expressing the relation that are easy to pick up by word embeddings.
• dc.description.sponsorship This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 715154) and the DFG (SFB 732, Project D10).
• dc.format.mimetype application/pdf
• dc.identifier.citation Gupta A, Boleda G, Pado S. Distributed prediction of relations for entities: the easy, the difficult, and the impossible. In: Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017); 2017 Aug 3-4; Vancouver, Canada. Stroudsburg (PA): ACL; 2017. p. 104–9.
• dc.identifier.uri http://hdl.handle.net/10230/35534
• dc.language.iso eng
• dc.publisher ACL (Association for Computational Linguistics)ca
• dc.relation.ispartof Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017); 2017 Aug 3-4; Vancouver, Canada. Stroudsburg (PA): ACL; 2017. p. 104–9.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/715154
• dc.rights © ACL, Creative Commons Attribution 4.0 License
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Computational linguistics
• dc.subject.keyword Natural language processing
• dc.subject.keyword Computational semantics
• dc.subject.keyword Distributional semantics
• dc.subject.keyword Reference
• dc.subject.keyword Entities
• dc.title Distributed prediction of relations for entities: the Easy, the Difficult, and the impossibleca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion