Global Reasoning over Database Structures for Text-to-SQL Parsing

Ben Bogin, Matt Gardner, Jonathan Berant


Abstract
State-of-the-art semantic parsers rely on auto-regressive decoding, emitting one symbol at a time. When tested against complex databases that are unobserved at training time (zero-shot), the parser often struggles to select the correct set of database constants in the new database, due to the local nature of decoding. %since their decisions are based on weak, local information only. In this work, we propose a semantic parser that globally reasons about the structure of the output query to make a more contextually-informed selection of database constants. We use message-passing through a graph neural network to softly select a subset of database constants for the output query, conditioned on the question. Moreover, we train a model to rank queries based on the global alignment of database constants to question words. We apply our techniques to the current state-of-the-art model for Spider, a zero-shot semantic parsing dataset with complex databases, increasing accuracy from 39.4% to 47.4%.
Anthology ID:
D19-1378
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
3659–3664
Language:
URL:
https://aclanthology.org/D19-1378
DOI:
10.18653/v1/D19-1378
Bibkey:
Cite (ACL):
Ben Bogin, Matt Gardner, and Jonathan Berant. 2019. Global Reasoning over Database Structures for Text-to-SQL Parsing. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3659–3664, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Global Reasoning over Database Structures for Text-to-SQL Parsing (Bogin et al., EMNLP-IJCNLP 2019)
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PDF:
https://preview.aclanthology.org/auto-file-uploads/D19-1378.pdf
Attachment:
 D19-1378.Attachment.pdf
Code
 benbogin/spider-schema-gnn-global