@inproceedings{ezquerro-etal-2025-hierarchical,
title = "Hierarchical Bracketing Encodings for Dependency Parsing as Tagging",
author = {Ezquerro, Ana and
Vilares, David and
Yli-Jyr{\"a}, Anssi and
G{\'o}mez-Rodr{\'i}guez, Carlos},
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-long.903/",
doi = "10.18653/v1/2025.acl-long.903",
pages = "18436--18450",
ISBN = "979-8-89176-251-0",
abstract = "We present a family of encodings for sequence labeling dependency parsing, based on the concept of hierarchical bracketing. We show that the existing 4-bit projective encoding belongs to this family, but it is suboptimal in the number of labels used to encode a tree. We derive an optimal hierarchical bracketing, which minimizes the number of symbols used and encodes projective trees using only 12 distinct labels (vs. 16 for the 4-bit encoding). We also extend optimal hierarchical bracketing to support arbitrary non-projectivity in a more compact way than previous encodings. Our new encodings yield competitive accuracy on a diverse set of treebanks."
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<abstract>We present a family of encodings for sequence labeling dependency parsing, based on the concept of hierarchical bracketing. We show that the existing 4-bit projective encoding belongs to this family, but it is suboptimal in the number of labels used to encode a tree. We derive an optimal hierarchical bracketing, which minimizes the number of symbols used and encodes projective trees using only 12 distinct labels (vs. 16 for the 4-bit encoding). We also extend optimal hierarchical bracketing to support arbitrary non-projectivity in a more compact way than previous encodings. Our new encodings yield competitive accuracy on a diverse set of treebanks.</abstract>
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%0 Conference Proceedings
%T Hierarchical Bracketing Encodings for Dependency Parsing as Tagging
%A Ezquerro, Ana
%A Vilares, David
%A Yli-Jyrä, Anssi
%A Gómez-Rodríguez, Carlos
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-251-0
%F ezquerro-etal-2025-hierarchical
%X We present a family of encodings for sequence labeling dependency parsing, based on the concept of hierarchical bracketing. We show that the existing 4-bit projective encoding belongs to this family, but it is suboptimal in the number of labels used to encode a tree. We derive an optimal hierarchical bracketing, which minimizes the number of symbols used and encodes projective trees using only 12 distinct labels (vs. 16 for the 4-bit encoding). We also extend optimal hierarchical bracketing to support arbitrary non-projectivity in a more compact way than previous encodings. Our new encodings yield competitive accuracy on a diverse set of treebanks.
%R 10.18653/v1/2025.acl-long.903
%U https://aclanthology.org/2025.acl-long.903/
%U https://doi.org/10.18653/v1/2025.acl-long.903
%P 18436-18450
Markdown (Informal)
[Hierarchical Bracketing Encodings for Dependency Parsing as Tagging](https://aclanthology.org/2025.acl-long.903/) (Ezquerro et al., ACL 2025)
ACL
- Ana Ezquerro, David Vilares, Anssi Yli-Jyrä, and Carlos Gómez-Rodríguez. 2025. Hierarchical Bracketing Encodings for Dependency Parsing as Tagging. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 18436–18450, Vienna, Austria. Association for Computational Linguistics.