We explore and improve the capabilities of LLMs to generate data for
grammatical error correction (GEC). When merely producing parallel sentences,
their patterns are too simplistic to be valuable as a corpus. To address this
issue, we propose an automated framework that includes a Subject Selector,
Grammar Selector, Prompt Manager, and Evaluator. Additionally, we introduce a
new dataset for GEC tasks, named \textbf{ChatLang-8}, which encompasses eight
types of subject nouns and 23 types of grammar. It consists of 1 million pairs
featuring human-like grammatical errors. Our experiments reveal that ChatLang-8
exhibits a more uniform pattern composition compared to existing GEC datasets.
Furthermore, we observe improved model performance when using ChatLang-8
instead of existing GEC datasets. The experimental results suggest that our
framework and ChatLang-8 are valuable resources for enhancing ChatGPT's data
generation capabilities.

我们探索和改进 LLM 的能力，以生成语法错误纠正（GEC）的数据，提出了一个自动化框架，并引入了一个名为 ChatLang-8 的新数据集，该数据集包含八种主题名词和 23 种语法类型，实验结果表明我们的框架和 ChatLang-8 对于提高 ChatGPT 的数据生成能力具有价值。