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.

本文提出了一个基于 ChatGPT 的零 - shot 文本到 SQL 的方法 ——C3，该方法在 Spider 数据集上的测试集上取得了 82.3% 的执行准确度，并成为了 Spider Challenge 的最优零 - shot 文本到 SQL 方法。C3 包括三个关键组件：Clear Prompting、Calibration with Hints 和 Consistent Output，分别对应于模型输入、模型偏差和模型输出。它为零 - shot 文本到 SQL 提供了系统性的处理方法。作者进行了广泛的实验验证了这种方法的有效性和效率。