HEAD-QA: A Healthcare Dataset for Complex Reasoning

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UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitle57th Annual Meeting of the Association for Computational Linguistics (ACL 2019)es_ES
UDC.departamentoLetrases_ES
UDC.endPage966es_ES
UDC.grupoInvLingua e Sociedade da Información (LYS)es_ES
UDC.journalTitleProceedings of the 57th Annual Meeting of the Association for Computational Linguisticses_ES
UDC.startPage960es_ES
dc.contributor.authorVilares, David
dc.contributor.authorGómez-Rodríguez, Carlos
dc.date.accessioned2024-05-24T12:25:14Z
dc.date.available2024-05-24T12:25:14Z
dc.date.issued2019-07
dc.descriptionTook place in Florence (Italy) at the 'Fortezza da Basso' from July 28th to August 2nd, 2019.es_ES
dc.description.abstract[Absctract]: We present HEAD-QA, a multi-choice question answering testbed to encourage research on complex reasoning. The questions come from exams to access a specialized position in the Spanish healthcare system, and are challenging even for highly specialized humans. We then consider monolingual (Spanish) and cross-lingual (to English) experiments with information retrieval and neural techniques. We show that: (i) HEAD-QA challenges current methods, and (ii) the results lag well behind human performance, demonstrating its usefulness as a benchmark for future work.es_ES
dc.description.sponsorshipThis work has received support from the TELEPARES-UDC project (FFI2014-51978-C2- 2-R) and the ANSWER-ASAP project (TIN2017- 85160-C2-1-R) from MINECO, from Xunta de Galicia (ED431B 2017/01), and from the European Research Council (ERC), under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150). We thank Mark Anderson for his help with translation fluency evaluation.es_ES
dc.description.sponsorshipXunta de Galicia; ED431B 2017/01es_ES
dc.identifier.citationDavid Vilares and Carlos Gómez-Rodríguez. 2019. HEAD-QA: A Healthcare Dataset for Complex Reasoning. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 960–966, Florence, Italy. Association for Computational Linguistics.es_ES
dc.identifier.urihttp://hdl.handle.net/2183/36616
dc.language.isoenges_ES
dc.publisherAssociation for Computational Linguisticses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/714150es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FFI2014-51978-C2-2-R/ES/TECNOLOGÍAS DE LA LENGUA PARA ANÁLISIS DE OPINIONES EN REDES SOCIALES: DEL TEXTO AL MICROTEXTOes_ES
dc.relation.projectIDinfo: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 PROFUNDOes_ES
dc.relation.urihttps://aclanthology.org/P19-1092/es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectHealthcare datasetes_ES
dc.subjectComplex reasoninges_ES
dc.subjectMulti-choice question answeringes_ES
dc.subjectCross-lingual experimentses_ES
dc.titleHEAD-QA: A Healthcare Dataset for Complex Reasoninges_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication37dabbe9-f54f-43bb-960e-0bf3ac7e54eb
relation.isAuthorOfPublicatione70a3969-39f6-4458-9339-3b71756fa56e
relation.isAuthorOfPublication.latestForDiscovery37dabbe9-f54f-43bb-960e-0bf3ac7e54eb

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