@inproceedings{ezquerro-etal-2024-dependency,
title = "Dependency Graph Parsing as Sequence Labeling",
author = "Ezquerro, Ana and
Vilares, David and
G{\'o}mez-Rodr{\'\i}guez, Carlos",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.659",
pages = "11804--11828",
abstract = "Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling. However, these approaches do not support more complex graph-based representations, such as semantic dependencies or enhanced universal dependencies, as they cannot handle reentrancy or cycles. By extending them, we define a range of unbounded and bounded linearizations that can be used to cast graph parsing as a tagging task, enlarging the toolbox of problems that can be solved under this paradigm. Experimental results on semantic dependency and enhanced UD parsing show that with a good choice of encoding, sequence-labeling semantic dependency parsers combine high efficiency with accuracies close to the state of the art, in spite of their simplicity.",
}
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%0 Conference Proceedings
%T Dependency Graph Parsing as Sequence Labeling
%A Ezquerro, Ana
%A Vilares, David
%A Gómez-Rodríguez, Carlos
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F ezquerro-etal-2024-dependency
%X Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling. However, these approaches do not support more complex graph-based representations, such as semantic dependencies or enhanced universal dependencies, as they cannot handle reentrancy or cycles. By extending them, we define a range of unbounded and bounded linearizations that can be used to cast graph parsing as a tagging task, enlarging the toolbox of problems that can be solved under this paradigm. Experimental results on semantic dependency and enhanced UD parsing show that with a good choice of encoding, sequence-labeling semantic dependency parsers combine high efficiency with accuracies close to the state of the art, in spite of their simplicity.
%U https://aclanthology.org/2024.emnlp-main.659
%P 11804-11828
Markdown (Informal)
[Dependency Graph Parsing as Sequence Labeling](https://aclanthology.org/2024.emnlp-main.659) (Ezquerro et al., EMNLP 2024)
ACL
- Ana Ezquerro, David Vilares, and Carlos Gómez-Rodríguez. 2024. Dependency Graph Parsing as Sequence Labeling. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 11804–11828, Miami, Florida, USA. Association for Computational Linguistics.