Datasets:
Tasks:
Text Classification
Formats:
json
Sub-tasks:
entity-linking-classification
Size:
100K - 1M
ArXiv:
DOI:
License:
Upload README.md
Browse files
README.md
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license: []
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multilinguality:
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- multilingual
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pretty_name: 'doc2doc '
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size_categories:
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- 100K<n<1M
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source_datasets:
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https://huggingface.co/spaces/huggingface/datasets-tagging
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# Dataset Card for [
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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### Dataset Summary
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doc2doc is a multilingual, diachronic dataset of
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### Supported Tasks and Leaderboards
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```
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{
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}
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```
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### Data Fields
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```
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year: (int) the publication year
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text: (str) the facts of the case
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label: (class label) the judgment outcome: 0 (dismissal) or 1 (approval)
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language: (str) one of (de, fr, it)
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```
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### Data Splits
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The dataset was split date-stratisfied
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- Train: 2002-2015
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- Validation: 2016-
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- Test:
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| Language | Subset | Number of Documents (Training/Validation/Test) |
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| German | **de** |
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| French | **fr** |
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| Italian | **it** |
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## Dataset Creation
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#### Who are the source language producers?
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The
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### Annotations
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license: []
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multilinguality:
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- multilingual
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pretty_name: 'doc2doc information retrieval'
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size_categories:
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- 100K<n<1M
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source_datasets:
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https://huggingface.co/spaces/huggingface/datasets-tagging
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# Dataset Card for [doc2doc]
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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### Dataset Summary
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doc2doc is a multilingual, diachronic dataset of 130K Swiss Federal Supreme Court (FSCS) cases annotated with law citations and ruling citations, posing a challenging text classification task. As unique label we are using decision_id of cited rulings and uuid of cited law articles, which can be found in the SwissCourtRulingCorpus. We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case, to promote robustness and fairness studies on the critical area of legal NLP.
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### Supported Tasks and Leaderboards
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```
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{
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"decision_id": ,
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"language": de,
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"year": 2018,
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"chamber": ,
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"court": ,
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"canton": ,
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"region": ,
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"origin_chamber": ,
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"origin_court": ,
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"origin_canton": ,
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"law_area": ,
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"law_sub_area": ,
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"laws": ,
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"cited_rulings": ,
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"facts": ,
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"considerations": ,
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"rulings": ,
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"origin_facts": ,
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"origin_considerations": ,
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}
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```
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### Data Fields
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```
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decision_id: (str) a unique identifier of the for the document
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language: (str) one of (de, fr, it)
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year: (int) the publication year
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chamber: (str) the chamber of the case
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court: (str) the court of the case
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canton: (str) the canton
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region: (str) the region of the case
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origin_chamber: (str) the chamber of the origin case
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origin_court: (str) the court of the origin case
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origin_canton: (str) the canton of the origin case
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law_area: (str) the law area of the case
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law_sub_area:(str) the law sub area of the case
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laws: (str) a list of laws as example: ['art. 34 CPP', 'art. 32 CPP']
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cited rulings: (str) a list of cited rulings as example: ["BGE 124 II 234", "BGE 145 III 23"]
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facts: (str) the facts of the case
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considerations: (str) the considerations of the case
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rulings: (str) the rulings of the case
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origin_facts: (str) the facts of the origin case
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origin_considerations: (str) the considerations of the origin case
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```
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### Data Splits
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The dataset was split date-stratisfied
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- Train: 2002-2015
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- Validation: 2016-2017
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- Test: 2018-2022
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| Language | Subset | Number of Documents (Training/Validation/Test) |
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|------------|------------|--------------------------------------------|
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| German | **de** | / / |
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| French | **fr** | / / |
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| Italian | **it** | / / |
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## Dataset Creation
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#### Who are the source language producers?
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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.
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### Annotations
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