@inproceedings{kato-matsubara-2021-new,
title = "A New Representation for Span-based {CCG} Parsing",
author = "Kato, Yoshihide and
Matsubara, Shigeki",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.826",
doi = "10.18653/v1/2021.emnlp-main.826",
pages = "10579--10584",
abstract = "This paper proposes a new representation for CCG derivations. CCG derivations are represented as trees whose nodes are labeled with categories strictly restricted by CCG rule schemata. This characteristic is not suitable for span-based parsing models because they predict node labels independently. In other words, span-based models may generate invalid CCG derivations that violate the rule schemata. Our proposed representation decomposes CCG derivations into several independent pieces and prevents the span-based parsing models from violating the schemata. Our experimental result shows that an off-the-shelf span-based parser with our representation is comparable with previous CCG parsers.",
}
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<abstract>This paper proposes a new representation for CCG derivations. CCG derivations are represented as trees whose nodes are labeled with categories strictly restricted by CCG rule schemata. This characteristic is not suitable for span-based parsing models because they predict node labels independently. In other words, span-based models may generate invalid CCG derivations that violate the rule schemata. Our proposed representation decomposes CCG derivations into several independent pieces and prevents the span-based parsing models from violating the schemata. Our experimental result shows that an off-the-shelf span-based parser with our representation is comparable with previous CCG parsers.</abstract>
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%0 Conference Proceedings
%T A New Representation for Span-based CCG Parsing
%A Kato, Yoshihide
%A Matsubara, Shigeki
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F kato-matsubara-2021-new
%X This paper proposes a new representation for CCG derivations. CCG derivations are represented as trees whose nodes are labeled with categories strictly restricted by CCG rule schemata. This characteristic is not suitable for span-based parsing models because they predict node labels independently. In other words, span-based models may generate invalid CCG derivations that violate the rule schemata. Our proposed representation decomposes CCG derivations into several independent pieces and prevents the span-based parsing models from violating the schemata. Our experimental result shows that an off-the-shelf span-based parser with our representation is comparable with previous CCG parsers.
%R 10.18653/v1/2021.emnlp-main.826
%U https://aclanthology.org/2021.emnlp-main.826
%U https://doi.org/10.18653/v1/2021.emnlp-main.826
%P 10579-10584
Markdown (Informal)
[A New Representation for Span-based CCG Parsing](https://aclanthology.org/2021.emnlp-main.826) (Kato & Matsubara, EMNLP 2021)
ACL
- Yoshihide Kato and Shigeki Matsubara. 2021. A New Representation for Span-based CCG Parsing. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10579–10584, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.