five

TSHR-MR/echr_facts

收藏
Hugging Face2024-09-01 更新2025-11-03 收录
下载链接:
https://hf-mirror.com/datasets/TSHR-MR/echr_facts
下载链接
链接失效反馈
官方服务:
资源简介:
--- dataset_info: features: - name: id dtype: int64 - name: labels dtype: string - name: judgment_facts dtype: string - name: replaced_countries dtype: string - name: one_hot_labels sequence: int64 splits: - name: train num_bytes: 154260079 num_examples: 15689 download_size: 71010918 dataset_size: 154260079 configs: - config_name: default data_files: - split: train path: data/train-* --- # European Court of Human Rights Dataset This dataset collects roughly 15,000 cases from the European Court of Human Rights' database - HUDOC. It utilizes regex to scrape through judgment facts and then applies Large Language Models (LLMs) to obtain the relevant violation(s) of the European Convention on Human Rights. The dataset contains any violation of the European Court of Human Rights that does not pertain to the Court's functioning. Instead, the violations included deal exclusively with substantive or procedural rights. This dataset also attempts to remove paragraph numbering wherever possible to provide cleaner text for analysis. ## Columns - **id**: Unique ID labels. - **judgment_facts**: The text between the "Facts" heading and the next relevant heading that indicates the end of the facts section, which is variable. - **replaced_countries**: A list of countries that have been replaced in the original text by `<COUNTRY>`. - **one_hot_labels**: The one-hot encoded labels for the 30 violations`. ## Purpose The purpose of this dataset is to assist in multilabel classification. ## Label to ECtHR Article Index {'P1': 0, 'P4': 1, 'P6': 2, 'P7': 3, '1': 4, '2': 5, '3': 6, '4': 7, '5': 8, '6': 9, '7': 10, '8': 11, '9': 12, '10': 13, '11': 14, '12': 15, '13': 16, '14': 17, '15': 18, '18': 19, '25': 20, '34': 21, '37': 22, '38': 23, '39': 24, '41': 25, '44': 26, '46': 27, '50': 28, '': 29}
提供机构:
TSHR-MR
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作