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JuDDGES/pl-court-raw

Dataset Card for JuDDGES/pl-court-raw Dataset Summary The dataset consists of Polish Court judgments available at https://orzeczenia.ms.gov.pl/, containing full content of the judgments along with metadata sourced from official API and extracted from the judgment contents. This dataset contains raw data. For instruction dataset see JuDDGES/pl-court-instruct. For graph dataset see JuDDGES/pl-court-graph. Supported Tasks and Leaderboards The dataset… See the full description on the dataset page: https://huggingface.co/datasets/JuDDGES/pl-court-raw.

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Dataset Card

Dataset Card for JuDDGES/pl-court-raw

Table of Contents

Dataset Description

  • —Homepage: TBA
  • —Repository: https://github.com/pwr-ai/JuDDGES
  • —Paper: TBA
  • —Point of Contact: lukasz.augustyniak@pwr.edu.pl; jakub.binkowski@pwr.edu.pl; albert.sawczyn@pwr.edu.pl

Dataset Summary

The dataset consists of Polish Court judgments available at https://orzeczenia.ms.gov.pl/, containing full content of the judgments along with metadata sourced from official API and extracted from the judgment contents. This dataset contains raw data. For instruction dataset see `JuDDGES/pl-court-instruct`. For graph dataset see `JuDDGES/pl-court-graph`.

Supported Tasks and Leaderboards

The dataset can be used for various tasks. However, it contains raw data acquired from official API, and we rather recommend using instruction dataset `JuDDGES/pl-court-instruct` for straightforward usage.

Languages

pl-PL Polish

Dataset Structure

Data Fields

FieldDescriptionType
sourceSource of the data, can be one of: [pl-court, nsa]String
judgment_idunique identifier of the judgmentString
docket_numbersignature of judgment (unique within court)String
judgment_datedate of judgmentDatetime(timeunit='us', timezone=None)
publication_datedate of judgment publicationDatetime(timeunit='us', timezone=None)
last_updatedate of last update of judgmentDatetime(timeunit='us', timezone=None)
court_idsystem unique identifier of the courtString
department_idsystem unique identifier of the court's departmentString
judgment_typetype of the judgment (one of)String
excerptFirst 500 characters of the judgmentString
xml_contentFull content of judgment in XML formatString
presiding_judgechairman judge nameString
decisiondecisionNull
judgeslist of judge names participating in the judgmentList(String)
legal_baseslegal acts which are bases for the judgmentList(String)
publishername of the person publishing the judgmentString
recordername of the person recording the judgmentString
revisername of the person revising the judgmentString
keywordslist of phrases representing the themes/topics of the judgmentList(String)
num_pagesnumber of pages in the judgmentInt64
full_textfull text of the judgmentString
volume_numbervolume numberInt64
volume_typetype of volumeString
court_namename of the court where the judgment was madeString
department_namename of the department within the court where the judgment was madeString
extractedlegalbasestextual representation of the legal bases for the judgment (with references to online repository)List(Struct({'address': String, 'art': String, 'isap_id': String, 'text': String, 'title': String}))
referencesPlain-text references to legal actsList(String)
thesisthesis of the judgmentString
countrythe country of origin of the judgment (one of [Poland, England])String
court_typetype of the court (one of ['ordinary court', 'administrative court', 'crown court'])String

Data Splits

This dataset is not split into subsets. The dataset has only train split.

Dataset Creation

For details on the dataset creation, see the paper [TBA]() and the code repository here.

Curation Rationale

Created to enable cross-jurisdictional legal analytics.

Source Data

Initial Data Collection and Normalization
  1. 1.Download judgments metadata.
  2. 2.Download judgments text (XML content of judgments).
  3. 3.Download additional details available for each judgment.
  4. 4.Map id of courts and departments to court name.
  5. 5.Extract raw text from XML content and details of judgments not available through API.
  6. 6.For further processing prepare local dataset dump in parquet file, version it with dvc and push to remote storage.
Who are the source language producers?

Produced by human legal professionals (judges, court clerks). Demographics was not analysed. Sourced from public court databases.

Annotations

Annotation process

No annotation was performed by us. All features were provided via API (anonymization and publication of the data were performed by court employees).

Who are the annotators?

As above.

Personal and Sensitive Information

Pseudoanonymized to comply with GDPR (art. 4 sec. 5 GDPR).

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 license the actual packaging of these data under Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

Citation Information

TBA

Statistics

Dataset size

Dataset size: 437_450 examples

Missing values

Field nameNull countNull fraction
source00
judgment_id00
docket_number00
judgment_date00
publication_date00
last_update00
court_id00
department_id00
judgment_type00
excerpt00
xml_content750
presiding_judge515130.12
decision4374501
judges433350.1
legal_bases1239340.28
publisher6290
recorder1135510.26
reviser1820
keywords1275080.29
num_pages00
full_text00
volume_number00
volume_type00
court_name14910
department_name14910
extractedlegalbases00
references437350.1
thesis3957560.9
country00
court_type00

Analysis of selected fields

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