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dc.contributor.authorFernández-González, Daniel
dc.contributor.authorGómez-Rodríguez, Carlos
dc.date.accessioned2024-01-24T08:34:42Z
dc.date.available2024-01-24T08:34:42Z
dc.date.issued2020-07
dc.identifier.citationDaniel Fernández-González and Carlos Gómez-Rodríguez. 2020. Transition-based Semantic Dependency Parsing with Pointer Networks. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7035–7046, Online. Association for Computational Linguistics. doi: 10.18653/v1/2020.acl-main.629es_ES
dc.identifier.urihttp://hdl.handle.net/2183/35100
dc.description.abstract[Abstract]: Transition-based parsers implemented with Pointer Networks have become the new state of the art in dependency parsing, excelling in producing labelled syntactic trees and outperforming graph-based models in this task. In order to further test the capabilities of these powerful neural networks on a harder NLP problem, we propose a transition system that, thanks to Pointer Networks, can straightforwardly produce labelled directed acyclic graphs and perform semantic dependency parsing. In addition, we enhance our approach with deep contextualized word embeddings extracted from BERT. The resulting system not only outperforms all existing transition-based models, but also matches the best fully-supervised accuracy to date on the SemEval 2015 Task 18 datasets among previous state-of-the-art graph-based parsers.es_ES
dc.description.sponsorshipThis work has received funding from the European Research Council (ERC), under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150), from the ANSWER-ASAP project (TIN2017-85160-C2-1-R) from MINECO, and from Xunta de Galicia (ED431B 2017/01, ED431G 2019/01).es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2017/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.language.isoenges_ES
dc.publisherAssociation for Computational Linguistics (ACL)es_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/714150es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-85160-C2-1-R/ES/AVANCES EN NUEVOS SISTEMAS DE EXTRACCION DE RESPUESTAS CON ANALISIS SEMANTICO Y APRENDIZAJE PROFUNDO/es_ES
dc.relation.urihttps://doi.org/10.18653/v1/2020.acl-main.629es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectComputational linguisticses_ES
dc.subjectDirected graphses_ES
dc.subjectGraphic methodses_ES
dc.subjectNatural language processing systemses_ES
dc.subjectSemantic Webes_ES
dc.subjectSyntacticses_ES
dc.subjectTrees (mathematics)es_ES
dc.titleTransition-based Semantic Dependency Parsing with Pointer Networkses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.startPage7035es_ES
UDC.endPage7046es_ES
dc.identifier.doi10.18653/v1/2020.acl-main.629
UDC.conferenceTitle58th Annual Meeting of the Association for Computational Linguisticses_ES


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