--- dataset_info: - config_name: de_de features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 202072546.78114817 num_examples: 13550 - name: validation num_bytes: 3387377.5166666666 num_examples: 137 - name: test num_bytes: 5094957.671779141 num_examples: 207 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 108293386 dataset_size: 210562732.1918162 - config_name: de_fr features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 202072546.78114817 num_examples: 13550 - name: validation num_bytes: 3387377.5166666666 num_examples: 137 - name: test num_bytes: 5094957.671779141 num_examples: 207 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 108523462 dataset_size: 210562732.1918162 - config_name: de_it features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 202072546.78114817 num_examples: 13550 - name: validation num_bytes: 3387377.5166666666 num_examples: 137 - name: test num_bytes: 5094957.671779141 num_examples: 207 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 108473921 dataset_size: 210562732.1918162 - config_name: default features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 892325523 num_examples: 59835 - name: validation num_bytes: 14835230 num_examples: 600 - name: test num_bytes: 24071829 num_examples: 978 - name: one_shot_examples num_bytes: 70652 num_examples: 9 download_size: 179083051 dataset_size: 931303234 - config_name: fr_de features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 81365890.42346452 num_examples: 5456 - name: validation num_bytes: 1359896.0833333333 num_examples: 55 - name: test num_bytes: 2633625.463190184 num_examples: 107 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 43156709 dataset_size: 85367262.19221026 - config_name: fr_fr features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 81365890.42346452 num_examples: 5456 - name: validation num_bytes: 1359896.0833333333 num_examples: 55 - name: test num_bytes: 2633625.463190184 num_examples: 107 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 43139753 dataset_size: 85367262.19221026 - config_name: fr_it features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 81365890.42346452 num_examples: 5456 - name: validation num_bytes: 1359896.0833333333 num_examples: 55 - name: test num_bytes: 2633625.463190184 num_examples: 107 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 43139791 dataset_size: 85367262.19221026 - config_name: it_de features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 14003403.795387315 num_examples: 939 - name: validation num_bytes: 197803.06666666668 num_examples: 8 - name: test num_bytes: 295359.86503067485 num_examples: 12 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 7557831 dataset_size: 14504416.949306877 - config_name: it_fr features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 14003403.795387315 num_examples: 939 - name: validation num_bytes: 197803.06666666668 num_examples: 8 - name: test num_bytes: 295359.86503067485 num_examples: 12 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 7562708 dataset_size: 14504416.949306877 - config_name: it_it features: - name: sample_id dtype: int64 - name: decision_id dtype: string - name: decision dtype: string - name: decision_language dtype: string - name: headnote dtype: string - name: headnote_language dtype: string - name: law_area dtype: string - name: year dtype: int64 - name: volume dtype: string - name: url dtype: string splits: - name: train num_bytes: 14003403.795387315 num_examples: 939 - name: validation num_bytes: 197803.06666666668 num_examples: 8 - name: test num_bytes: 295359.86503067485 num_examples: 12 - name: one_shot_examples num_bytes: 7850.222222222223 num_examples: 1 download_size: 7559305 dataset_size: 14504416.949306877 configs: - config_name: de_de data_files: - split: train path: de_de/train-* - split: validation path: de_de/validation-* - split: test path: de_de/test-* - split: one_shot_examples path: de_de/one_shot_examples-* - config_name: de_fr data_files: - split: train path: de_fr/train-* - split: validation path: de_fr/validation-* - split: test path: de_fr/test-* - split: one_shot_examples path: de_fr/one_shot_examples-* - config_name: de_it data_files: - split: train path: de_it/train-* - split: validation path: de_it/validation-* - split: test path: de_it/test-* - split: one_shot_examples path: de_it/one_shot_examples-* - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* - split: one_shot_examples path: data/one_shot_examples-* - config_name: fr_de data_files: - split: train path: fr_de/train-* - split: validation path: fr_de/validation-* - split: test path: fr_de/test-* - split: one_shot_examples path: fr_de/one_shot_examples-* - config_name: fr_fr data_files: - split: train path: fr_fr/train-* - split: validation path: fr_fr/validation-* - split: test path: fr_fr/test-* - split: one_shot_examples path: fr_fr/one_shot_examples-* - config_name: fr_it data_files: - split: train path: fr_it/train-* - split: validation path: fr_it/validation-* - split: test path: fr_it/test-* - split: one_shot_examples path: fr_it/one_shot_examples-* - config_name: it_de data_files: - split: train path: it_de/train-* - split: validation path: it_de/validation-* - split: test path: it_de/test-* - split: one_shot_examples path: it_de/one_shot_examples-* - config_name: it_fr data_files: - split: train path: it_fr/train-* - split: validation path: it_fr/validation-* - split: test path: it_fr/test-* - split: one_shot_examples path: it_fr/one_shot_examples-* - config_name: it_it data_files: - split: train path: it_it/train-* - split: validation path: it_it/validation-* - split: test path: it_it/test-* - split: one_shot_examples path: it_it/one_shot_examples-* license: cc task_categories: - summarization language: - de - fr - it tags: - legal pretty_name: Swiss Landmark Decision Summarization size_categories: - 10K", "decision_language": "de", "headnote": "", "headnote_language": "fr", "law_area": "administrative law and public international law", "year": 1980, "volume": "I", "url": "" } ``` --- ## Data Splits The dataset is chronologically split to prevent leakage of stylistic or temporal trends: | Split | Years | # Decisions | # Samples | Language Distribution | |-------|------------|-------------|-----------|------------------------| | Train | 1954–2021 | ~20K | ~60K | DE: 67.9%, FR: 27.4%, IT: 4.7% | | Val | 2022 | 200 | 600 | DE: 68.5%, FR: 27.5%, IT: 4.0% | | Test | 2023–2024 | 326 | 978 | DE: 63.5%, FR: 32.8%, IT: 3.7% | ## Dataset Configurations The dataset provides multiple configurations: - `default` contains all decision–headnote pairs combined (≈ 60k samples). - Pairwise configs (e.g., `de_fr`, `fr_it`, `it_de`) restrict to a specific decision language (`xx`) and a specific headnote language (`yy`). For example, `de_fr` contains German decisions with French headnotes. - Each decision appears three times across configs, once per headnote language. ## One-shot Examples Each config includes a small `one_shot_examples` split. These are predefined samples selected from validation to serve as prompting examples in few-shot settings, as described in the paper. --- ## Dataset Creation ### Curation Rationale The dataset was created to provide a real-world multilingual legal benchmark for abstractive summarization. Unlike legislative corpora (e.g., EUR-Lex), SLDS focuses on case law, emphasizing concise and legally authoritative headnotes. ### Source Data - **Collection**: Decisions were scraped from the official SFSC archive ([bger.ch](https://www.bger.ch)). - **Coverage**: 70 years (1954–2024), covering all five legal volumes (I–V). - **Processing**: - Extracted full decision text and multilingual headnotes. - Normalized metadata (year, volume, law area). - Applied language detection and formatting. - Structured into decision–headnote pairs for training and evaluation. ### Who are the source language producers? Decisions and headnotes are written by judges and clerks of the Swiss Federal Supreme Court, the highest judicial body in Switzerland. --- ## Annotations - **Annotation Process**: Headnotes are official summaries, authored by clerks and judges, not crowdsourced. - **Annotators**: Legal experts at the SFSC. - **Metadata**: Derived from official publication metadata. --- ## Personal and Sensitive Information The dataset consists of publicly available legal documents. The SFSC applies strict anonymization guidelines before publication to protect personal data: [Anonymisierungsregeln](https://www.bger.ch/files/live/sites/tfl/files/pdf/Reglemente/Anonymisierungsregeln_2020_d.pdf). --- ## Considerations for Using the Data ### Social Impact SLDS supports multilingual access to Swiss case law, enabling legal professionals, researchers, and NLP systems to work across language barriers. It may assist in legal information retrieval, case comparison, and legal education. ### Discussion of Biases - **Language imbalance**: German dominates the dataset, reflecting its prevalence in Swiss court proceedings. - **Legal domain distribution**: Some law areas (e.g., criminal law and criminal procedure) are more frequent, potentially biasing models. - **Stylistic rigidity**: Headnotes follow legal drafting conventions that may not generalize to other summarization domains. ### Other Known Limitations - Headnotes are highly formulaic, which can lead to overfitting. - **Cross-lingual evaluation** may be skewed by differences in legal phrasing traditions across languages. - **Evaluation metrics** such as ROUGE may not fully capture legal correctness. --- ## Licensing Information Released under **[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)**. --- ## Citation Information If you use SLDS in your work, please cite: ```bibtex @inproceedings{rolshoven-etal-2025-unlocking, title = "Unlocking Legal Knowledge: A Multilingual Dataset for Judicial Summarization in {S}witzerland", author = {Rolshoven, Luca and Rasiah, Vishvaksenan and Bose, Srinanda Br{\"u}gger and Hostettler, Sarah and Burkhalter, Lara and St{\"u}rmer, Matthias and Niklaus, Joel}, editor = "Christodoulopoulos, Christos and Chakraborty, Tanmoy and Rose, Carolyn and Peng, Violet", booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025", month = nov, year = "2025", address = "Suzhou, China", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2025.findings-emnlp.832/", pages = "15382--15411", ISBN = "979-8-89176-335-7", } ```