遇见数据集

openlegaldata/legal-citation-graph-germany

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Hugging Face2026-05-22 更新2026-05-31 收录
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--- license: odbl dataset_info: - config_name: dump-20260520 features: - name: from_case_court_chamber dtype: string - name: from_case_court_city dtype: string - name: from_case_court_jurisdiction dtype: string - name: from_case_court_level_of_appeal dtype: string - name: from_case_court_name dtype: string - name: from_case_court_state dtype: string - name: from_case_date dtype: date32 - name: from_case_file_number dtype: string - name: from_case_review_status dtype: string - name: from_case_source_name dtype: string - name: from_case_type dtype: string - name: from_law_book_slug dtype: string - name: from_slug dtype: string - name: from_type dtype: string - name: to_case_court_jurisdiction dtype: string - name: to_case_court_level_of_appeal dtype: string - name: to_case_court_name dtype: string - name: to_law_book_code dtype: string - name: to_law_book_slug dtype: string - name: to_law_section dtype: string - name: to_law_title dtype: string - name: to_slug dtype: string - name: to_type dtype: string splits: - name: train num_bytes: 2019159004 num_examples: 7438459 download_size: 72720810 dataset_size: 2019159004 - config_name: dump-20260520-10k features: - name: from_case_court_chamber dtype: string - name: from_case_court_city dtype: string - name: from_case_court_jurisdiction dtype: string - name: from_case_court_level_of_appeal dtype: string - name: from_case_court_name dtype: string - name: from_case_court_state dtype: string - name: from_case_date dtype: date32 - name: from_case_file_number dtype: string - name: from_case_review_status dtype: string - name: from_case_source_name dtype: string - name: from_case_type dtype: string - name: from_law_book_slug dtype: string - name: from_slug dtype: string - name: from_type dtype: string - name: to_case_court_jurisdiction dtype: string - name: to_case_court_level_of_appeal dtype: string - name: to_case_court_name dtype: string - name: to_law_book_code dtype: string - name: to_law_book_slug dtype: string - name: to_law_section dtype: string - name: to_law_title dtype: string - name: to_slug dtype: string - name: to_type dtype: string splits: - name: train num_bytes: 2722440 num_examples: 10000 download_size: 583880 dataset_size: 2722440 - config_name: dump-20260520-1k features: - name: from_case_court_chamber dtype: string - name: from_case_court_city dtype: string - name: from_case_court_jurisdiction dtype: string - name: from_case_court_level_of_appeal dtype: string - name: from_case_court_name dtype: string - name: from_case_court_state dtype: string - name: from_case_date dtype: date32 - name: from_case_file_number dtype: string - name: from_case_review_status dtype: string - name: from_case_source_name dtype: string - name: from_case_type dtype: string - name: from_law_book_slug dtype: string - name: from_slug dtype: string - name: from_type dtype: string - name: to_case_court_jurisdiction dtype: string - name: to_case_court_level_of_appeal dtype: string - name: to_case_court_name dtype: string - name: to_law_book_code dtype: string - name: to_law_book_slug dtype: string - name: to_law_section dtype: string - name: to_law_title dtype: string - name: to_slug dtype: string - name: to_type dtype: string splits: - name: train num_bytes: 271033 num_examples: 1000 download_size: 83828 dataset_size: 271033 configs: - config_name: dump-20260520 data_files: - split: train path: dump-20260520/train-* - config_name: dump-20260520-10k data_files: - split: train path: dump-20260520-10k/train-* - config_name: dump-20260520-1k data_files: - split: train path: dump-20260520-1k/train-* --- # Open Legal Data: Citation Graph Germany This dataset contains the citation graph extracted from German court decisions and laws indexed by the [Open Legal Data Platform](https://de.openlegaldata.io). Each row is a single citation edge from a source (case or law) to a target (case or law), with the slugs needed to join back to the [`court-decisions-germany`](https://huggingface.co/datasets/openlegaldata/court-decisions-germany) dataset. ## Available dumps | Date | Configs | | --- | --- | | 2026-05-20 | `dump-20260520`, `dump-20260520-10k`, `dump-20260520-1k` | ## Data format Each sample has the following columns: - `from_type` — ``Case`` or ``Law`` (source side) - `from_slug` — slug of the citing object - `from_law_book_slug` — book slug when ``from_type == "Law"``; empty otherwise - `from_case_*` — court / file number / date / etc. when ``from_type == "Case"`` - `to_type` — ``Case`` or ``Law`` (target side) - `to_slug` — slug of the cited object - `to_law_book_slug`, `to_law_book_code`, `to_law_section`, `to_law_title` — populated for Law targets - `to_case_court_*` — populated for Case targets Numerical IDs are intentionally omitted — slugs are sufficient and stable across snapshot dates. ## Discord > [!NOTE] > We're back! This project is getting a fresh update - join us on [Discord](https://discord.gg/WCy3aq25ZF) to help revive it. ## Citation If you use this data, please cite our [research paper](https://arxiv.org/abs/2005.13342): ```bibtex @inproceedings{10.1145/3383583.3398616, author = {Ostendorff, Malte and Blume, Till and Ostendorff, Saskia}, title = {Towards an Open Platform for Legal Information}, year = {2020}, isbn = {9781450375856}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3383583.3398616}, doi = {10.1145/3383583.3398616}, booktitle = {Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020}, pages = {385–388}, numpages = {4}, keywords = {open data, open source, legal information system, legal data}, location = {Virtual Event, China}, series = {JCDL '20} } ``` ## License In Germany, acts, statutory instruments, official decrees and official notices, as well as decisions (including court decisions) and official head notes of decisions do not enjoy copyright protection (UrhG § 5). The collection and metadata has the Open Database License (ODbL) v1.0.

This dataset contains the citation graph extracted from German court decisions and laws indexed by the Open Legal Data Platform. Each row is a single citation edge from a source (case or law) to a target (case or law), with the slugs needed to join back to the court-decisions-germany dataset. It includes multiple versions such as dump-20260520 (full), dump-20260520-10k (10k samples), and dump-20260520-1k (1k samples). Columns include from_type (source type, e.g., case or law), from_slug (slug of the citing object), from_case_* columns (court, file number, date, etc. when source is a case), to_type (target type), to_slug (slug of the cited object), to_law_* columns (book information when target is a law), and to_case_court_* columns (court information when target is a case). The dataset is based on German laws that do not enjoy copyright protection and is licensed under the Open Database License (ODbL) v1.0.

提供机构:
openlegaldata
搜集汇总
数据集介绍
openlegaldata/legal-citation-graph-germany 数据集图片
构建方式
该数据集依托Open Legal Data平台,对德国法院裁判文书与法律条文之间的引用关系进行系统性抽取与结构化建模。构建过程以裁判文书和法律文本为起点,识别其中所载的规范性或判例性引证,将每一组引用关系抽象为一条有向边,形成以案例与法律为节点的引用图。每条引用边均保留源对象与目标对象的类型、标识符及必要的法院、法条元数据,并借助稳定的slug字段实现与court-decisions-germany数据集的关联。数据集按快照日期提供完整版、万条版与千条版三种配置,以适应不同规模的研究需求。
特点
数据集以引用边为基本单元,覆盖案例与法律两类节点之间的复杂引证网络,囊括源侧法院层级、管辖区域、裁判日期、案号以及目标侧法条书名、条款、标题等多维元数据。字段设计有意省略数值型标识符,依托slug实现跨快照的稳定关联,显著提升数据可复现性与长期可维护性。完整配置包含逾743万条引用边,数据体量约2GB,同时提供万条与千条精简版本,兼顾大规模分析与快速验证。数据以ODbL许可开放,来源符合德国著作权法对官方文本的豁免规定。
使用方法
研究者可通过HuggingFace datasets库按配置名称加载相应数据分片,例如选择dump-20260520获取全量引用图,或选用dump-20260520-1k进行快速探索。加载后,可利用from_slug与to_slug字段将引用边与court-decisions-germany数据集中的裁判文书进行连接,从而在文本与图结构之间建立对应关系。基于源侧与目标侧的法院、法条元数据,可开展引证网络分析、法律效力评估、裁判说理模式挖掘等任务。数据以有向边形式组织,可直接导入NetworkX等图分析工具进行中心性、社区发现或路径追踪研究。
背景与挑战
背景概述
在司法信息化与法律实证研究蓬勃发展的背景下,德国开放法律数据平台(Open Legal Data Platform)构建了法律引文图谱数据集legal-citation-graph-germany,旨在系统刻画德国法院裁判与成文法之间的引用关系。该数据集由Malte Ostendorff、Till Blume与Saskia Ostendorff等研究人员于2020年前后依托开放法律信息平台建设项目创建,其核心研究问题在于打破法律文献的封闭壁垒,以开放数据推动法律检索、裁判预测与法律网络分析。凭借逾740万条引用边的大规模覆盖,该数据集为法律信息检索、引文网络分析和计算法学研究提供了关键基础设施,对推动法律数据的可复现研究具有显著影响力。
当前挑战
该数据集所应对的领域问题在于法律引文关系的自动抽取与结构化表示:裁判文书与成文法条之间的引用往往以自由文本形式出现,格式高度异质且缺乏统一标识,难以直接用于大规模网络分析。构建过程中的挑战亦不容忽视,包括从异构法院裁判中准确识别引用来源与目标、区分案件与法律两类引用实体、保持不同快照日期之间标识的稳定性,以及处理法律文本中引用表述的歧义与省略。与此同时,数据覆盖的完整性与时效性受制于来源平台的索引范围,跨州与跨审级裁判的引用规范差异亦对图谱的一致性构成持续挑战。
常用场景
经典使用场景
在计算法学与法律信息检索领域,裁判文书间的引证关系构成了司法知识演化的脉络。legal-citation-graph-germany数据集以边表形式记录了德国法院裁判与成文法律之间的引用关系,每条记录标识了引用方与被引用方的类型、法院层级、案号及法条编号等元数据。其经典用法在于构建法律引证网络,支撑引文推荐、裁判要旨检索与法律问答系统的训练。研究者可借助from_slug与to_slug字段将引证边与court-decisions-germany裁判文书数据集关联,形成从文本到网络结构的完整分析链路,并利用1k、10k与全量dump等不同规模的配置开展可扩展性实验。
解决学术问题
该数据集直面法律信息学中裁判引证关系缺乏结构化、大规模且开放获取数据这一瓶颈。过往研究多依赖商业数据库或小规模人工标注,难以支撑可复现的量化分析。此数据集以七百余万条引证边覆盖德国各级法院与联邦法律,使得引证网络分析、法律条文适用模式挖掘、法院层级影响力测度等议题得以在开放数据基础上展开。其意义在于将法律引证研究从封闭语料推向可验证、可扩展的开放科学范式,为跨法域比较研究与司法透明度评估提供了公共基础设施。
衍生相关工作
该数据集衍生于Open Legal Data平台的开源实践,其研究脉络可追溯至Ostendorff等人发表的Towards an Open Platform for Legal Information一文,该工作系统阐述了德国法律信息开放平台的数据架构与引证抽取方法。在此基础上,后续研究围绕德国裁判文书的引证网络分析、法律条文共现模式挖掘以及跨语言法律检索等方向展开。数据集与court-decisions-germany的slug关联设计,也催生了将引证结构与裁判全文联合建模的探索,为法律自然语言处理中的引文推荐、判决预测等任务提供了结构化的监督信号。
以上内容由遇见数据集搜集并总结生成
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