Fast semantic parsing with well-typedness guarantees

Matthias Lindemann, Jonas Groschwitz, Alexander Koller


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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.emnlp-main.323.pdf
Video:
 https://slideslive.com/38939114
Code
 coli-saar/am-parser