Abstract
AM dependency parsing is a linguistically principled method for neural semantic parsing with high accuracy across multiple graphbanks. It relies on a type system that models semantic valency but makes existing parsers slow. We describe an A* parser and a transition-based parser for AM dependency parsing which guarantee well-typedness and improve parsing speed by up to 3 orders of magnitude, while maintaining or improving accuracy.- Anthology ID:
- 2020.emnlp-main.323
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3929–3951
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.323
- DOI:
- 10.18653/v1/2020.emnlp-main.323
- Cite (ACL):
- Matthias Lindemann, Jonas Groschwitz, and Alexander Koller. 2020. Fast semantic parsing with well-typedness guarantees. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 3929–3951, Online. Association for Computational Linguistics.
- Cite (Informal):
- Fast semantic parsing with well-typedness guarantees (Lindemann et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2020.emnlp-main.323.pdf
- Code
- coli-saar/am-parser