Testing Cross-Database Semantic Parsers With Canonical Utterances
Heather Lent, Semih Yavuz, Tao Yu, Tong Niu, Yingbo Zhou, Dragomir Radev, Xi Victoria Lin
Abstract
The benchmark performance of cross-database semantic parsing has climbed steadily in recent years, catalyzed by the wide adoption of pre-trained language models. Yet existing work have shown that state-of-the-art cross-database semantic parsers struggle to generalize to novel user utterances, databases and query structures. To obtain transparent details on the strengths and limitation of these models, we propose a diagnostic testing approach based on controlled synthesis of canonical natural language and SQL pairs. Inspired by the CheckList, we characterize a set of essential capabilities for cross-database semantic parsing models, and detailed the method for synthesizing the corresponding test data. We evaluated a variety of high performing models using the proposed approach, and identified several non-obvious weaknesses across models (e.g. unable to correctly select many columns). Our dataset and code are released as a test suite at http://github.com/hclent/BehaviorCheckingSemPar.- Anthology ID:
- 2021.eval4nlp-1.8
- Volume:
- Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Yang Gao, Steffen Eger, Wei Zhao, Piyawat Lertvittayakumjorn, Marina Fomicheva
- Venue:
- Eval4NLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 73–83
- Language:
- URL:
- https://aclanthology.org/2021.eval4nlp-1.8
- DOI:
- 10.18653/v1/2021.eval4nlp-1.8
- Cite (ACL):
- Heather Lent, Semih Yavuz, Tao Yu, Tong Niu, Yingbo Zhou, Dragomir Radev, and Xi Victoria Lin. 2021. Testing Cross-Database Semantic Parsers With Canonical Utterances. In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems, pages 73–83, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Testing Cross-Database Semantic Parsers With Canonical Utterances (Lent et al., Eval4NLP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.eval4nlp-1.8.pdf
- Code
- hclent/behaviorcheckingsempar