Dataset Card for truthful qa Table of Contents Dataset Card for truthful qa Table of Contents Dataset Description Dataset Summary Supported Tasks and Leaderboards Languages Dataset Structure Data Instances generation multiple choice Data Fields generation multiple choice Data Splits Dataset Creation Curation Rationale Source Data Initial Data Collection and Normalization Who are the source language producers? Annotations Annotation process Who are the annotators? Personal and Sensitive Information Considerations for Using the Data Social Impact of Dataset Discussion of Biases Other Known Limitations Additional Information Dataset Curators Licensing Information Citation Information Contributions Dataset Description Homepage: [Needs More Information] Repository: https://github.com/sylinrl/TruthfulQA Paper: https://arxiv.org/abs/2109.07958 Leaderboard: [Needs More Information] Point of Contact: [Needs More Information] Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some h…
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