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Dataset Card for Swiss Court View Generation

Dataset Summary

Swiss Judgment Prediction is a multilingual, diachronic dataset of 329K Swiss Federal Supreme Court (FSCS) cases. This dataset is part of a challenging text generation task.

Supported Tasks and Leaderboards

Languages

Switzerland has four official languages with three languages German, French and Italian being represented. The decisions are written by the judges and clerks in the language of the proceedings.

Language Subset Number of Documents Full
German de 160K
French fr 128K
Italian it 41K

Dataset Structure

Data Fields

- decision_id: unique identifier for the decision
- facts: facts section of the decision
- considerations: considerations section of the decision
- label: label of the decision
- law_area: area of law of the decision
- language: language of the decision
- year: year of the decision
- court: court of the decision
- chamber: chamber of the decision
- canton: canton of the decision
- region: region of the decision

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

Dataset Creation

Curation Rationale

Source Data

Initial Data Collection and Normalization

The original data are published from the Swiss Federal Supreme Court (https://www.bger.ch) in unprocessed formats (HTML). The documents were downloaded from the Entscheidsuche portal (https://entscheidsuche.ch) in HTML.

Who are the source language producers?

The decisions are written by the judges and clerks in the language of the proceedings.

Annotations

Annotation process

Who are the annotators?

Metadata is published by the Swiss Federal Supreme Court (https://www.bger.ch).

Personal and Sensitive Information

The dataset contains publicly available court decisions from the Swiss Federal Supreme Court. Personal or sensitive information has been anonymized by the court before publication according to the following guidelines: https://www.bger.ch/home/juridiction/anonymisierungsregeln.html.

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

We release the data under CC-BY-4.0 which complies with the court licensing (https://www.bger.ch/files/live/sites/bger/files/pdf/de/urteilsveroeffentlichung_d.pdf) © Swiss Federal Supreme Court, 2002-2022

The copyright for the editorial content of this website and the consolidated texts, which is owned by the Swiss Federal Supreme Court, is licensed under the Creative Commons Attribution 4.0 International licence. This means that you can re-use the content provided you acknowledge the source and indicate any changes you have made. Source: https://www.bger.ch/files/live/sites/bger/files/pdf/de/urteilsveroeffentlichung_d.pdf

Citation Information

Please cite our ArXiv-Preprint

@misc{rasiah2023scale,
      title={SCALE: Scaling up the Complexity for Advanced Language Model Evaluation}, 
      author={Vishvaksenan Rasiah and Ronja Stern and Veton Matoshi and Matthias Stürmer and Ilias Chalkidis and Daniel E. Ho and Joel Niklaus},
      year={2023},
      eprint={2306.09237},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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