# C3: Zero-shot Text-to-SQL with ChatGPT

**Authors:** Xuemei Dong, Chao Zhang, Yuhang Ge, Yuren Mao, Yunjun Gao, lu Chen, Jinshu Lin, Dongfang Lou  
**arXiv:** [2307.07306](https://arxiv.org/abs/2307.07306)  
**Date:** 2023-07-14  
**Summary page:** https://www.summarizepaper.com/fr/paper/2307.07306v1/

## 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.