The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
Open accessAbstract
We present a neural approach called IRNet for complex and cross-domain Text-to-SQL.IR-Net aims to address two challenges: 1) the mismatch between intents expressed in natural language (NL) and the implementation details in SQL; 2) the challenge in predicting columns caused by the large number of outof-domain words.Instead of end-to-end synthesizing a SQL query, IRNet decomposes the synthesis process into three phases.In the first phase, IRNet performs a schema linking over a question and a database schema.Then, IRNet adopts a grammar-based neural model to synthesize a SemQL query which is an intermediate representation that we design to bridge NL and SQL.Finally, IRNet deterministically infers a SQL query from the synthesized SemQL query with domain knowledge.On the challenging Text-to-SQL benchmark Spider, IRNet achieves 46.7% accuracy, obtaining 19.5% absolute improvement over previous state-of-the-art approaches.At the time of writing, IRNet achieves the first position on the Spider leaderboard. * Equal Contributions. Work done during an internship at MSRA.NL: Show the names of students who have a grade higher than 5 and have at least 2 friends. SQL: SELECT T1.name FROM friend AS T1 JOIN highschooler AS T2ON T1.student_id = T2.idWHERE T2
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Cited by
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
Wang, B., Shin, R., Liu, X., Polozov, O., & Richardson, M. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.677 · Cited by 512
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
Yin, P., Neubig, G., Yih, W.-T., & Riedel, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.745 · Cited by 487
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Gao, D., Wang, H., Li, Y., Sun, X., Qian, Y., Ding, B., & Zhou, J. (2024) · Proceedings of the VLDB Endowment · doi:10.14778/3641204.3641221 · Cited by 342
Li, J., Hui, B., Qu, G., Yang, J., Li, B., Li, B., Wang, B., Qin, B., Cao, R., Geng, R., et al. (2023) · arXiv · doi:10.48550/arxiv.2305.03111 · Cited by 278
Semantic Evaluation for Text-to-SQL with Distilled Test Suites
Zhong, R., Yu, T., & Klein, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.29 · Cited by 112
Metadata
- Authors
- Guo, J., Zhan, Z., Gao, Y., Xiao, Y., Lou, J.-G., Liu, T., & Zhang, D.
- Venue
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Published
- 2019
- Pages
- 4524-4535
- OpenAlex
- W2945102109
- Cited by
- 406
- References
- 52
- FWCI
- 18.53
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- Guo, J., Zhan, Z., Gao, Y., Xiao, Y., Lou, J.-G., Liu, T., & Zhang, D. (2019). Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. https://doi.org/10.18653/v1/p19-1444
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