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Discontinuous Constituent Parsing as Sequence Labeling
| dc.contributor.author | Vilares, David | |
| dc.contributor.author | Gómez-Rodríguez, Carlos | |
| dc.date.accessioned | 2024-05-23T09:21:21Z | |
| dc.date.available | 2024-05-23T09:21:21Z | |
| dc.date.issued | 2020-11 | |
| dc.identifier.citation | David Vilares and Carlos Gómez-Rodríguez. 2020. Discontinuous Constituent Parsing as Sequence Labeling. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 2771–2785, Online. Association for Computational Linguistics. | es_ES |
| dc.identifier.uri | http://hdl.handle.net/2183/36592 | |
| dc.description | EMNLP2020 took place online from November 16 – 20 2020 | es_ES |
| dc.description.abstract | [Absctract]: This paper reduces discontinuous parsing to sequence labeling. It first shows that existing reductions for constituent parsing as labeling do not support discontinuities. Second, it fills this gap and proposes to encode tree discontinuities as nearly ordered permutations of the input sequence. Third, it studies whether such discontinuous representations are learnable. The experiments show that despite the architectural simplicity, under the right representation, the models are fast and accurate. | es_ES |
| dc.description.sponsorship | We thank Maximin Coavoux for giving us access to the data used in this work. We acknowledge the European Research Council (ERC), which has funded this research under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150), MINECO (ANSWER-ASAP, TIN2017-85160-C2- 1-R), Xunta de Galicia (ED431C 2020/11), and Centro de Investigacion de Galicia ”CITIC”, ´ funded by Xunta de Galicia and the European Union (European Regional Development FundGalicia 2014-2020 Program), by grant ED431G 2019/01. | es_ES |
| dc.description.sponsorship | Xunta de Galicia; ED431C 2020/11 | es_ES |
| dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Association for Computational Linguistics | es_ES |
| dc.relation | info:eu-repo/grantAgreement/EC/H2020/714150 | es_ES |
| dc.relation | info: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.uri | https://aclanthology.org/2020.emnlp-main.221.pdf | es_ES |
| dc.rights | Atribución 3.0 España | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
| dc.subject | Discontinuous Constituent Parsing | es_ES |
| dc.subject | Sequence Labeling | es_ES |
| dc.subject | Tree Discontinuities | es_ES |
| dc.subject | Neural transducer | es_ES |
| dc.title | Discontinuous Constituent Parsing as Sequence Labeling | es_ES |
| dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
| dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
| dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
| UDC.journalTitle | Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) | es_ES |
| UDC.startPage | 2771 | es_ES |
| UDC.endPage | 2785 | es_ES |
| UDC.conferenceTitle | 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) | es_ES |
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