metadata

license: cc-by-sa-4.0

Only a small part of the actual dataset for testing purposes uploaded at the moment.

Law Area Prediction

Introduction

The main subset contains cases to be classified into the four main areas of law: Public, Civil, Criminal and Social

A portion of the cases from the main areas Public, Civil and Criminal can be classified further into sub-areas:

"public": ['Tax', 'Urban Planning and Environmental', 'Expropriation', 'Public Administration', 'Other Fiscal'],
"civil": ['Rental and Lease', 'Employment Contract', 'Bankruptcy', 'Family', 'Competition and Antitrust', 'Intellectual Property'],
'criminal': ['Substantive Criminal', 'Criminal Procedure']

Size

Load datasets

Load the main dataset:

dataset = load_dataset("rcds/law_area_prediction")

Load the dataset with the sub-areas of Civil law:

dataset = load_dataset("rcds/law_area_prediction", "civil")

Columns

Main dataset

decision_id: unique identifier for the decision
facts: facts section of the decision
considerations: considerations section of the decision
label: label of the decision (main area of law)
law_sub_area: sub area of law of the decision
language: language of the decision
year: year of the decision
court: court of the decision
chamber: chamber of the decision
canton: canton of the decision
region: region of the decision

Sub-area dataset

decision_id: unique identifier for the decision
facts: facts section of the decision
considerations: considerations section of the decision
law_area: label of the decision (main area of law)
label: sub area of law of the decision
language: language of the decision
year: year of the decision
court: court of the decision
chamber: chamber of the decision
canton: canton of the decision
region: region of the decision