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---
configs:
- config_name: press_release
data_files:
- split: train
path: text_level/train.parquet
- split: validation
path: text_level/val.parquet
- split: test
path: text_level/test.parquet
task_categories:
- translation
language:
- de
- fr
- it
tags:
- legal
- press release
pretty_name: Swiss Supreme Court Press Release Translations
size_categories:
- 1K<n<10K
---
# Dataset Card for Swiss Supreme Court Press Release Translations
This dataset card describes a collection of press releases from the Swiss Federal Supreme Court, provided in German, French, and Italian. It is a parallel dataset enabling multilingual translation and analysis of legal press releases.
## Dataset Details
### Dataset Description
This dataset consists of press releases from the Swiss Federal Supreme Court in three official languages: German, French, and Italian. Each release provides essential information on recent decisions, legal updates, and notable cases. The dataset supports multilingual tasks and can be used for machine translation, text alignment, or legal document processing and analysis.
- **Curated by:** Joel Niklaus
- **Source:** Swiss Federal Supreme Court Press Releases
- **Language(s) (NLP):** German (de), French (fr), Italian (it)
- **License:** [More Information Needed]
### Dataset Sources
- **Repository:** https://github.com/JoelNiklaus/SwissLegalTranslations
- **Paper [optional]:** [SwiLTra-Bench: The Swiss Legal Translation Benchmark](https://arxiv.org/abs/2503.01372)
- **Demo [optional]:** [More Information Needed]
## Uses
### Direct Use
This dataset can be used for:
- Multilingual text alignment and translation tasks across three languages.
- Language model training or fine-tuning for press releases in the legal domain.
### Out-of-Scope Use
The dataset may not be suitable for tasks outside the legal domain, or those that do not consider the context of press releases.
## Dataset Structure
The dataset consists of three fields per entry, providing multilingual translations of each press release.
- Fields:
- `filename`: Unique filename identifying each press release.
- `de_text`: Press release content in German.
- `fr_text`: Press release content in French.
- `it_text`: Press release content in Italian.
### Example Code
```python
from datasets import load_dataset
# Load the press release dataset
press_release_dataset = load_dataset('joelniklaus/SwissSupremeCourtPressReleases', name='press_release', trust_remote_code=True)
# Print dataset for inspection
print(press_release_dataset)
```
## Dataset Creation
### Curation Rationale
The dataset was created to support multilingual legal research and media analysis. By providing structured press releases in three languages, it enables a variety of tasks in legal translation and text processing.
### Source Data
The dataset is derived from publicly available Swiss Supreme Court press releases.
#### Data Collection and Processing
The press releases were collected, cleaned, and structured in German, French, and Italian. Each release is saved in a standardized format with a unique filename.
#### Who are the source data producers?
The source data is produced by the Swiss Federal Supreme Court.
### Annotations [optional]
No additional annotations have been added beyond the official translations provided by Swiss authorities.
#### Personal and Sensitive Information
The dataset does not contain any personal, sensitive, or private information. It consists solely of publicly available press releases.
## Bias, Risks, and Limitations
The dataset is specific to Swiss federal press releases and may not represent international press releases or general legal frameworks outside Switzerland. Users should consider these limitations for cross-national legal studies.
### Recommendations
This dataset is best used for tasks within the legal and media domains, especially those focused on multilingual press release processing, translation, and analysis.
## Citation [optional]
**BibTeX:**
If you find this dataset helpful, feel free to cite our publication [SwiLTra-Bench: The Swiss Legal Translation Benchmark](https://arxiv.org/abs/2503.01372):
```
@misc{niklaus2025swiltrabenchswisslegaltranslation,
title={SwiLTra-Bench: The Swiss Legal Translation Benchmark},
author={Joel Niklaus and Jakob Merane and Luka Nenadic and Sina Ahmadi and Yingqiang Gao and Cyrill A. H. Chevalley and Claude Humbel and Christophe Gösken and Lorenzo Tanzi and Thomas Lüthi and Stefan Palombo and Spencer Poff and Boling Yang and Nan Wu and Matthew Guillod and Robin Mamié and Daniel Brunner and Julio Pereyra and Niko Grupen},
year={2025},
eprint={2503.01372},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2503.01372},
}
```
**APA:**
Niklaus, J., Merane, J., Nenadic, L., Ahmadi, S., Gao, Y., Chevalley, C. A. H., Humbel, C., Gösken, C., Tanzi, L., Lüthi, T., Palombo, S., Poff, S., Yang, B., Wu, N., Guillod, M., Mamié, R., Brunner, D., Pereyra, J., & Grupen, N. (2025). SwiLTra-Bench: The Swiss Legal Translation Benchmark. arXiv. https://arxiv.org/abs/2503.01372
## Glossary [optional]
- **Swiss Federal Supreme Court**: The highest court in Switzerland responsible for federal legal matters.
## More Information [optional]
[More Information Needed]
## Dataset Card Authors
Joel Niklaus
## Dataset Card Contact
[Joel Niklaus](mailto:[email protected]) |