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NL2SQL with partial missing metadata based on multi-view metadata graph compensation and reasoning

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Abstract

The performance of metadata-dependent NL2SQL models will be seriously decreased, while facing the incomplete or distorted metadata information. In response to this problem, we proposed a metadata compensation approach, which represents the question together with SQL query, data cell value relevance and incomplete schema data as a global metadata graph, and applies knowledge graph reasoning to complete the metadata graph. This global metadata graph is a multi-graph. An improved transR model was proposed to represent this multi-graph by integrating the contributions from multiple relationships between two nodes. Depending on the compensated metadata graph, new end-to-end and preprocess improving frameworks were respectively constructed for adapting to different metadata-dependent NL2SQL systems. The new models have been evaluated on Spider dataset with artificially simulated partial metadata relation deficiency or metadata distortion. Except ablation comparing, the new models also have been compared with some approaches of existing and have demonstrated improved performance.

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Acknowledgements

This work is supported by Sichuan Province Science and Technology Support Program, No.: 2020YFS0090, 2020ZHCG0078, 2021YFN0117, 2022YFS0135; Medico Engineering Cooperation Funds from university of Electronic Science and Technology of China No.: ZYGX2021YGLH011.

Funding

This work is supported by Sichuan Province Science and Technology Support Program, No.: 2020YFS0090, 2020ZHCG0078, 2021YFN0117, 2022YFS0135; Medico Engineering Cooperation Funds from university of Electronic Science and Technology of China No.: ZYGX2021YGLH011.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Laboratory of Intelligent Collaborative Computing, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Jie Lin, Yulong Liang, Jiyan Li, Yi Bai & Yong Wang

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  1. Jie Lin
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  2. Yulong Liang
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  3. Jiyan Li
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Contributions

Conceptualization: Jie Lin; Methodology: Jie Lin, JiYan Li; Formal analysis and investigation: Jie Lin, YuLong Liang, JiYan Li, Yi Bai, Yong Wang; Software : JiYan Li, YuLong Liang; Writing - original draft preparation: Jie Lin, JiYan Li, YuLong Liang, Yi Bai, Yong Wang; Writing - review and editing: Jie Lin, YuLong Liang, JiYan Li, Yi Bai, Yong Wang; Funding acquisition:Jie Lin; Validation: Yi Bai, YuLong Liang, Yong Wang.

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Correspondence to Jie Lin.

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Lin, J., Liang, Y., Li, J. et al. NL2SQL with partial missing metadata based on multi-view metadata graph compensation and reasoning. Appl Intell 54, 1511–1524 (2024). https://doi.org/10.1007/s10489-023-05221-z

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