--- language: - en - zh license: cc-by-sa-4.0 task_categories: - multiple-choice pretty_name: LogiQA2.0 data_splits: - train - validation - test dataset_info: config_name: logiqa2_zh features: - name: answer dtype: int32 - name: text dtype: string - name: question dtype: string - name: options sequence: string splits: - name: train num_bytes: 8820627 num_examples: 12751 - name: test num_bytes: 1087414 num_examples: 1594 - name: validation num_bytes: 1107666 num_examples: 1593 download_size: 7563394 dataset_size: 11015707 configs: - config_name: logiqa2_zh data_files: - split: train path: logiqa2_zh/train-* - split: test path: logiqa2_zh/test-* - split: validation path: logiqa2_zh/validation-* --- # Dataset Card for Dataset Name ## Dataset Description - **Homepage:** https://github.com/csitfun/LogiQA2.0, https://github.com/csitfun/LogiEval - **Repository:** https://github.com/csitfun/LogiQA2.0, https://github.com/csitfun/LogiEval - **Paper:** https://ieeexplore.ieee.org/abstract/document/10174688 ### Dataset Summary Logiqa2.0 dataset - logical reasoning in MRC and NLI tasks LogiEval: a benchmark suite for testing logical reasoning abilities of instruct-prompt large language models ### Licensing Information Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. ### Citation Information @ARTICLE{10174688, author={Liu, Hanmeng and Liu, Jian and Cui, Leyang and Teng, Zhiyang and Duan, Nan and Zhou, Ming and Zhang, Yue}, journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing}, title={LogiQA 2.0 — An Improved Dataset for Logical Reasoning in Natural Language Understanding}, year={2023}, volume={}, number={}, pages={1-16}, doi={10.1109/TASLP.2023.3293046}} @misc{liu2023evaluating, title={Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4}, author={Hanmeng Liu and Ruoxi Ning and Zhiyang Teng and Jian Liu and Qiji Zhou and Yue Zhang}, year={2023}, eprint={2304.03439}, archivePrefix={arXiv}, primaryClass={cs.CL} }