Create README.md

README.md

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+---
+annotations_creators:
+- machine-generated
+language:
+- de
+- fr
+- it
+language_creators:
+- expert-generated
+license: []
+multilinguality:
+- multilingual
+pretty_name: Legal Criticality Prediction
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+tags: []
+task_categories:
+- text-classification
+---
+# Dataset Card for [legal criticality prediction]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+Legal Criticality Prediction (LCP) is a multilingual, diachronic dataset of 130K Swiss Federal Supreme Court (FSCS) cases annotated with two criticality labels. The bge_label i a binary label (critical, non-critical), while the citation label has 5 classes (critical-1, critical-2, critical-3, critical-4, non-critical). Critical classes of the citation_label are distinct subsets of the critical class of the bge_label. This dataset creates a challenging text classification task. We also provide additional metadata as the publication year, the law area and the canton of origin per case, to promote robustness and fairness studies on the critical area of legal NLP.
+
+### Supported Tasks and Leaderboards
+
+LCP can be used as text classification task
+
+### 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.
+German (80k), French (40k), Italian (10k)
+
+## Dataset Structure
+
+```
+{
+  "decision_id": ,
+  "language": de,
+  "year": 2018,
+  "chamber": ,
+  "court": ,
+  "canton": ,
+  "region": ,
+  "origin_chamber": ,
+  "origin_court": ,
+  "origin_canton": ,
+  "law_area": ,
+  "law_sub_area": ,
+  "bge_label": ,
+  "citation_label": ,
+  "facts": ,
+  "considerations": ,
+  "rulings": ,
+  "origin_facts": ,
+  "origin_considerations": ,
+}
+```
+
+### Data Fields
+
+```
+decision_id: (str) a unique identifier of the for the document
+language: (str) one of (de, fr, it)
+year: (int) the publication year
+chamber: (str) the chamber of the case
+court: (str) the court of the case
+canton: (str) the canton
+region: (str) the region of the case
+origin_chamber: (str) the chamber of the origin case
+origin_court: (str) the court of the origin case
+origin_canton:  (str) the canton of the origin case
+law_area: (str) the law area of the case
+law_sub_area:(str) the law sub area of the case
+bge_label: (str) critical or non-critical
+citation_label: (str) critical-1, critical-2, critical-3, critical-4, non-critical
+facts: (str) the facts of the case
+considerations: (str) the considerations of the case
+rulings: (str) the rulings of the case
+origin_facts: (str) the facts of the origin case
+origin_considerations: (str) the considerations of the origin case
+```
+
+### Data Instances
+[More Information Needed]
+### Data Fields
+[More Information Needed]
+### Data Splits
+
+The dataset was split date-stratisfied
+- Train: 2002-2015
+- Validation: 2016-2017
+- Test: 2018-2022
+
+| Language   | Subset     | Number of Documents (Training/Validation/Test) | 
+|------------|------------|--------------------------------------------|  
+| German     | **de**     |  /  /                          |
+| French     | **fr**     |  /  /                       |
+| Italian    | **it**     |  /  /                           |
+
+## Dataset Creation
+### Curation Rationale
+
+The dataset was curated by Stern et al. (2023).
+
+### 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
+
+bge_label:
+1. all bger_references in the bge header were extracted
+2. bger file_names are compared with the found references
+
+citation_label:
+1. count all citations for all bger cases and weight citations
+2. divide cited cases in four different classes, depending on amount of citations
+
+#### Who are the annotators?
+
+Ronja Stern annotated the citations.
+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
+
+*Visu, Ronja, Joel*
+*Title: Blabliblablu*
+*Name of conference*
+```
+cit
+```
+
+### Contributions
+
+Thanks to [@Stern5497](https://github.com/stern5497) for adding this dataset.