dataset_info:
features:
- name: demographic_category
dtype: string - name: demographic_group
dtype: string - name: context
dtype: string - name: context_en
dtype: string - name: sentence
dtype: string - name: sentence_en
dtype: string - name: context_label
dtype: string - name: context_sub_label
dtype: string - name: sentence_label
dtype: string - name: sentence_sub_label
sequence: string - name: annotated_demo
list:- name: demographic_category
dtype: string - name: demographic_group
sequence: string
splits:
- name: demographic_category
- name: train
num_bytes: 23587249
num_examples: 54393 - name: valid
num_bytes: 2956445
num_examples: 6799 - name: test
num_bytes: 2965863
num_examples: 6801
download_size: 13335660
dataset_size: 29509557
configs: - config_name: default
data_files:- split: train
path: data/train-* - split: valid
path: data/valid-* - split: test
path: data/test-*
license: mit
language:
- split: train
- ko
tags: - safety
reference: https://github.com/naver-ai/korean-safety-benchmarks
@inproceedings{lee2023kosbi,
title={KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application},
author={Hwaran Lee and Seokhee Hong and Joonsuk Park and Takyoung Kim and Gunhee Kim and Jung-Woo Ha},
booktitle={Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics: Industry Track},
year={2023}
}