nayohan/SQuARe-response

dataset_info:
features:

• name: question
  dtype: string
• name: question_en
  dtype: string
• name: response
  dtype: string
• name: response_en
  dtype: string
• name: acceptable?
  dtype: int64
• name: category
  sequence: string
• name: question_category
  dtype: string
• name: raw_annotations
  struct:
  • name: 'Q2: Acceptable or Non-acceptable'
    list:
    • name: acceptable?
      dtype: string
    • name: workerID
      dtype: int64
  • name: 'Q3-1: Reasons behind the non-acceptability'
    list:
    • name: category
      sequence: string
    • name: workerID
      dtype: int64
  • name: 'Q3-2: Reasons behind the acceptability'
    list:
    • name: category
      sequence: string
    • name: workerID
      dtype: int64

splits:

• name: train
  num_bytes: 9589383
  num_examples: 11952
• name: valid
  num_bytes: 9621758
  num_examples: 12000
• name: test
  num_bytes: 9589383
  num_examples: 11952
• name: test_ood
  num_bytes: 455205
  num_examples: 480
  download_size: 11618081
  dataset_size: 29255729
  configs:
• config_name: default
  data_files:
  • split: train
    path: data/train-*
  • split: valid
    path: data/valid-*
  • split: test
    path: data/test-*
  • split: test_ood
    path: data/test_ood-*
    license: mit
    language:
• ko
  tags:
• safety

reference: https://github.com/naver-ai/korean-safety-benchmarks

@inproceedings{lee2023square,
                title={SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created Through Human-Machine Collaboration}, 
                author={Hwaran Lee and Seokhee Hong and Joonsuk Park and Takyoung Kim and Meeyoung Cha and Yejin Choi and Byoung Pil Kim and Gunhee Kim and Eun-Ju Lee and Yong Lim and Alice Oh and Sangchul Park and Jung-Woo Ha},
                booktitle={Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics},
                year={2023}
}