C3: Zero-shot Text-to-SQL with ChatGPT
XueMei Dong, Chao Zhang, Yuhang Ge, YUREN MAO, Yunjun Gao, Lu Chen, Jinshu Lin, Dongfang Lou
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ReproduceCode
- github.com/bigbigwatermalon/c3sqlOfficialIn paperpytorch★ 167
Abstract
This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and becomes the state-of-the-art zero-shot Text-to-SQL method on the Spider Challenge. C3 consists of three key components: Clear Prompting (CP), Calibration with Hints (CH), and Consistent Output (CO), which are corresponding to the model input, model bias and model output respectively. It provides a systematic treatment for zero-shot Text-to-SQL. Extensive experiments have been conducted to verify the effectiveness and efficiency of our proposed method.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| spider | C3 + ChatGPT + Zero-Shot | Execution Accuracy (Test) | 82.3 | — | Unverified |