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

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dc.contributor.author Boleda, Gemma
dc.contributor.author Gupta, Abhijeet
dc.contributor.author Padó, Sebastian
dc.date.accessioned 2018-09-28T07:42:00Z
dc.date.available 2018-09-28T07:42:00Z
dc.date.issued 2017
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.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.language.iso eng
dc.publisher ACL (Association for Computational Linguistics)
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.rights © ACL, Creative Commons Attribution 4.0 License
dc.title Distributed prediction of relations for entities: the Easy, the Difficult, and the impossible
dc.type info:eu-repo/semantics/conferenceObject
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.relation.projectID info:eu-repo/grantAgreement/EC/H2020/715154
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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