I am a Strange Dataset

该数据集旨在测试语言模型处理元语言自我指涉的能力，要求模型生成并验证自我指涉的陈述。该数据集将示例分为与元语言理解相关的10个标签，并包含一个单独的挑战数据集，名为“我是一个不可能的数据集”。规模上，数据集包含208个示例（其中200个用于评估，3个用于少样本提示，5个用于入门任务，以及额外的10个示例）。任务内容涉及自我指涉陈述的生成与验证。

This dataset is designed to test the ability of language models to handle meta-linguistic self-reference, requiring models to generate and verify self-referential statements. It categorizes examples into 10 labels related to meta-linguistic understanding, and includes a separate challenge dataset titled "I Am an Impossible Dataset". In terms of scale, the dataset contains 208 examples: 200 for evaluation, 3 for few-shot prompting, 5 for introductory tasks, and an additional 10 examples. The task involves the generation and verification of self-referential statements.