KQA-Pro+QA2HALL dataset

This dataset is designed for the task of detecting hallucinations in text generated by large language models. It was created using the framework QA2HALL proposed in [1], which generates sentences containing synthetical hallucinations by using questions from a Knowledge Graph Question Answering (KGQA) dataset and incorrect answers generated by LLMs. The KGQA dataset used as the basis is KQA Pro (https://huggingface.co/datasets/drt/kqa_pro). For more details about the dataset and the framework, please refer to the paper and the framework's GitHub repository. File lists kqapro_qa2hall.json halucination detection dataset which was generated by applying QA2HALL on KQA Pro kqapro_filterd.json filterd version of KQA Pro (train and validation sets) for experiments in [1] We used this filtered version to construct "kqapro_qa2hall.json" README.md see this file for the format of the JSON files [1] Nakamura, K., Hasegawa, R., Otomura, K., Ichise, R., Hato, J.: QA2HALL: A Framework for Generating Non-trivial Hallucination Detection Datasets from KGQA Datasets. In: Proceedings of the 30th International Conference on Natural Language & Informations Systems (2025) (In preparation)