EasyQA is a GPT-3.5-turbo-generated dataset of easy kindergarten-level facts, meant to be used to prompt and evaluate large language models for "common sense" truthful responses. It was originally created to understand how different types of truthfulness may be represented in the intermediate activations of large language models. EasyQA compromises 2346 questions that span 50 categories, including art, technology, education, music, and animals. Questions are crafted to be extremely simple and obvious, eliciting an obvious truth that would not be susceptible to misconceptions.
