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# Dataset Card for [JuDDGES/en-court-raw](https://huggingface.co/datasets/JuDDGES/en-court-raw)
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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- [Statistics](#statistics)
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## Dataset Description
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- **Homepage: TBA**
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The dataset consists of England and Wales Appeal Court judgements available at https://caselaw.nationalarchives.gov.uk/judgments/advanced_search?court=ewca/crim/, containing full content of the judgements from official website. This dataset contains raw data.
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### Supported Tasks and Leaderboards
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[More Information Needed]
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### Languages
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en-EN English
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## Dataset Creation
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For details on the dataset
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### Curation Rationale
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1. Download judgements xml files.
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1. Extract raw text from XML content and details of judgments.
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1. For further processing prepare local dataset dump in parquet file, version it with
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#### Who are the source language producers?
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Produced by human legal professionals (judges, court clerks)
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### Annotations
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#### Annotation process
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#### Who are the annotators?
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As above.
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### Personal and Sensitive Information
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Pseudoanonymized to comply with GDPR (art. 4 sec. 5 GDPR).
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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## Statistics
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## Licensing Information
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We do not own any text from which these data and datasets have been extracted.
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We license the actual packaging of these data under the Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
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# Dataset Card for [JuDDGES/en-court-raw](https://huggingface.co/datasets/JuDDGES/en-court-raw)
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## Dataset Description
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- **Homepage: TBA**
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The dataset consists of England and Wales Appeal Court judgements available at https://caselaw.nationalarchives.gov.uk/judgments/advanced_search?court=ewca/crim/, containing full content of the judgements from official website. This dataset contains raw data.
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### Languages
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en-EN English
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## Dataset Creation
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For details on creating the dataset, see the paper [TBA]() and the code repository [here](https://github.com/pwr-ai/JuDDGES).
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### Curation Rationale
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1. Download judgements xml files.
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1. Extract raw text from XML content and details of judgments.
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1. For further processing, prepare a local dataset dump in a parquet file, version it with DVC, and push it to remote storage.
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#### Who are the source language producers?
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Produced by human legal professionals (judges, court clerks), it was not analyzed for demographics and was sourced from public court databases.
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### Annotations
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#### Annotation process
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We performed no annotation. All features were provided by the judiciary.uk
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#### Who are the annotators?
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As above.
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## Statistics
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{ width=400px }
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{ width=400px }
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{ width=400px }
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## Licensing Information
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We license the actual packaging of these data under Open Government Licence https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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