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.- Anthology ID:
- 2021.emnlp-main.826
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10579–10584
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-main.826
- DOI:
- 10.18653/v1/2021.emnlp-main.826
- Cite (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.
- Cite (Informal):
- A New Representation for Span-based CCG Parsing (Kato & Matsubara, EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2021.emnlp-main.826.pdf
- Code
- yosihide/span-based-ccg-derivation