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.

翻译：本文提出了一种基于ChatGPT的零样本Text-to-SQL方法，称为C3，其在Spider数据集保留测试集上的执行准确率达到82.3%，成为Spider挑战赛中性能最优的零样本Text-to-SQL方法。C3由三个关键组件构成：清晰提示（CP）、带提示的校准（CH）和一致性输出（CO），分别对应模型输入、模型偏差和模型输出。该方法为零样本Text-to-SQL任务提供了系统性解决方案。通过大量实验验证了所提方法的有效性和高效性。