Hierarchical Bracketing Encodings Work for Dependency Graphs

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UDC.coleccionInvestigación
UDC.conferenceTitleConference on Empirical Methods in Natural Language Processing (EMNLP 2025)
UDC.departamentoCiencias da Computación e Tecnoloxías da Información
UDC.endPage8851
UDC.grupoInvLingua e Sociedade da Información (LYS)
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación
UDC.startPage8838
dc.contributor.authorEzquerro, Ana
dc.contributor.authorGómez-Rodríguez, Carlos
dc.contributor.authorVilares, David
dc.date.accessioned2026-06-11T13:59:10Z
dc.date.available2026-06-11T13:59:10Z
dc.date.issued2025-11
dc.description.abstract[Abstract]: We revisit hierarchical bracketing encodings from a practical perspective in the context of dependency graph parsing. The approach encodes graphs as sequences, enabling linear-time parsing with n tagging actions, and still representing reentrancies, cycles, and empty nodes. Compared to existing graph linearizations, this representation substantially reduces the label space while preserving structural information. We evaluate it on a multilingual and multi-formalism benchmark, showing competitive results and consistent improvements over other methods in exact match accuracy.
dc.description.sponsorshipWe acknowledge grants GAP (PID2022- 139308OA-I00) funded by MICIU/AEI/10.13039/501100011033/ and ERDF, EU; LATCHING (PID2023-147129OB-C21) funded by MICIU/AEI/10.13039/501100011033 and ERDF, EU; and TSI-100925-2023-1 funded by Ministry for Digital Transformation and Civil Service and “NextGenerationEU” PRTR; as well as funding by Xunta de Galicia (ED431C 2024/02), and CITIC, as a center accredited for excellence within the Galician University System and a member of the CIGUS Network, receives subsidies from the Department of Education, Science, Universities, and Vocational Training of the Xunta de Galicia. Additionally, it is co-financed by the EU through the FEDER Galicia 2021-27 operational program (Ref. ED431G 2023/01)
dc.description.sponsorshipXunta de Galicia; ED431C 2024/02
dc.description.sponsorshipXunta de Galicia; ED431G 2023/01
dc.identifier.citationAna Ezquerro, Carlos Gómez-Rodríguez, and David Vilares. 2025. Hierarchical Bracketing Encodings Work for Dependency Graphs. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 8838–8851, Suzhou, China. Association for Computational Linguistics.
dc.identifier.doi10.18653/v1/2025.emnlp-main.447
dc.identifier.isbn979-889176332-6
dc.identifier.urihttps://hdl.handle.net/2183/48567
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022- 139308OA-I00/ES/REPRESENTACIONES ESTRUCTURADAS VERDES Y ENCHUFABLES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-147129OB-C21/ES/TECNOLOGIAS DEL LENGUAJE DESDE UNA PERSPECTIVA VERDE: DOMINIOS CON ESCASOS RECURSOS
dc.relation.urihttps://doi.org/10.18653/v1/2025.emnlp-main.447
dc.rights©2025 Association for Computational Linguistics
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDependency parsing
dc.subjectBracketing encodings
dc.subjectGraph linearization
dc.titleHierarchical Bracketing Encodings Work for Dependency Graphs
dc.typeconference output
dspace.entity.typePublication

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