README.md

---
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
  features:
  - name: id
    dtype: int32
  - name: answer
    dtype: int32
  - name: text
    dtype: string
  - name: type
    dtype: string
  - name: question
    dtype: string
  - name: options
    sequence: string
  splits:
  - name: train
    num_bytes: 13374480
    num_examples: 12567
  - name: test
    num_bytes: 1656534
    num_examples: 1572
  - name: validation
    num_bytes: 1687080
    num_examples: 1569
  download_size: 8538515
  dataset_size: 16718094
configs:
- config_name: logiqa2
  data_files:
  - split: train
    path: logiqa2/train-*
  - split: test
    path: logiqa2/test-*
  - split: validation
    path: logiqa2/validation-*
  default: true
---

# 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}
}