Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback

Ahmed Elgohary, Saghar Hosseini, Ahmed Hassan Awadallah

Abstract
We study the task of semantic parse correction with natural language feedback. Given a natural language utterance, most semantic parsing systems pose the problem as one-shot translation where the utterance is mapped to a corresponding logical form. In this paper, we investigate a more interactive scenario where humans can further interact with the system by providing free-form natural language feedback to correct the system when it generates an inaccurate interpretation of an initial utterance. We focus on natural language to SQL systems and construct, SPLASH, a dataset of utterances, incorrect SQL interpretations and the corresponding natural language feedback. We compare various reference models for the correction task and show that incorporating such a rich form of feedback can significantly improve the overall semantic parsing accuracy while retaining the flexibility of natural language interaction. While we estimated human correction accuracy is 81.5%, our best model achieves only 25.1%, which leaves a large gap for improvement in future research. SPLASH is publicly available at https://aka.ms/Splash_dataset.
Anthology ID:
2020.acl-main.187
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2065–2077
Language:
URL:
https://aclanthology.org/2020.acl-main.187
DOI:
10.18653/v1/2020.acl-main.187
Bibkey:
Cite (ACL):
Ahmed Elgohary, Saghar Hosseini, and Ahmed Hassan Awadallah. 2020. Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2065–2077, Online. Association for Computational Linguistics.
Cite (Informal):
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback (Elgohary et al., ACL 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/landing_page/2020.acl-main.187.pdf
Video:
 http://slideslive.com/38928802
Data
SPLASH, CoSQL, WikiSQL
PDF Search Video