Datasets:
license: cc-by-sa-4.0
task_categories:
- token-classification
language:
- de
- fr
- it
pretty_name: Swiss Citation Extraction
size_categories:
- 100K<n<1M
Dataset Card for Swiss Citation Extraction
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
Dataset Summary
Swiss Citation Extraction is a multilingual, diachronic dataset of 131K Swiss Federal Supreme Court (FSCS) cases. This dataset is part of a challenging token classification task.
Supported Tasks and Leaderboards
Languages
Switzerland has four official languages with three languages German, French and Italian being represenated. The decisions are written by the judges and clerks in the language of the proceedings.
| Language | Subset | Number of Documents |
|---|---|---|
| German | de | 85K |
| French | fr | 38K |
| Italian | it | 8K |
Dataset Structure
Data Fields
decision_id:
considerations:
NER_labels: CITATION = case citation or reference to another court decision; LAW = reference to a law; O = None of the previous two labels
law_area: (string)
language: (string)
year: (int64)
chamber: (string)
region: (string)
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}
}