Companion dataset and experiments to the arXiv preprint presenting the LaCour! subset Questions and Opinions.
To use the dataset, all you need is dataset_questions_opinions.json.
You can load the dataset e.g. with pandas:
import pandas as pd
df = pd.read_json('dataset_questions_opinions.json', dtype={'webcast_id': str})The dataset contains the following fields:
- webcast_id: the identifier for the associated hearing webcast, can be linked to the rest of the LaCour! corpus
- name: the name of the judge (only used to link question and opinion)
- has_question: the boolean value whether the judge had a question during the hearing
- has_opinion: the boolean value whether the judge had an opinion in the consequent judgment
- language: the language of the question
- question: the question asked by the judge
- case_id: the identifier for the relevant judgment document
- opinion: the tuple containing both the opinion title and the entire opinion by the judge
- opinion_type: the inferred type of the opinion (label), categorized into
PARTLY,DISSENTING,CONCURRING,OPINIONorUNKOWNif the type cannot be categorized
[To be updated] To create the dataset yourself, all relevant information has to be extracted first. For this please refer to the creation scripts in lacour-generation.
conda create -n lacour-qando python=3.9
conda activate lacour-qando
git clone https://github.com/trusthlt/lacour-qando.git
cd lacour-qando
pip install -r requirements.txt
[tbd]