metadata

license: cc-by-sa-4.0
dataset_info:
  - config_name: with_summaries
    features:
      - name: id
        dtype: string
      - name: type
        dtype: string
      - name: year
        dtype: string
      - name: input
        dtype: string
      - name: output
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        num_examples: 1521
      - name: validation
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      - name: test
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    download_size: 42168935
    dataset_size: 80143809
  - config_name: without_summaries
    features:
      - name: id
        dtype: string
      - name: type
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      - name: year
        dtype: string
      - name: input
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    splits:
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configs:
  - config_name: with_summaries
    data_files:
      - split: train
        path: with_summaries/train-*
      - split: validation
        path: with_summaries/validation-*
      - split: test
        path: with_summaries/test-*
  - config_name: without_summaries
    data_files:
      - split: all_data
        path: without_summaries/all_data-*

ZASCA-Sum: South African Supreme Court of Appeal Summarization Dataset

ZASCA-Sum is a curated dataset comprising over 4,000 judgments from the South African Supreme Court of Appeal (SCA), each paired with corresponding media summaries. This dataset is designed to facilitate research in legal natural language processing (NLP), particularly in the areas of legal summarization, information retrieval, and the development of legal language models tailored to South African jurisprudence.

Dataset Overview

Total Entries: 4,000+ judgment-summary pairs
Languages: English (South African legal context)
Structure:
- judgment_text: Full text of the SCA judgment
- media_summary: Corresponding media summary of the judgment
- case_id: Unique identifier for each case
- date: Date of the judgment
- url: Link to the official judgment document

Usage

This dataset is intended for:

Training and evaluating legal summarization models
Developing legal information retrieval systems
Conducting research in legal NLP and computational law
Enhancing access to legal information and promoting transparency in the judicial system

Accessing the Dataset

The dataset is available on Hugging Face:

👉 https://huggingface.co/datasets/dsfsi/zasca-sum

To load the dataset using the Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset("dsfsi/zasca-sum")

Citation

If you use ZASCA-Sum in your research, please cite the following publication:

@article{abdulmumin2025zasca,
  title={ZASCA-Sum: A Dataset of the South Africa Supreme Courts of Appeal Judgments and Media Summaries},
  author={Abdulmumin, Idris and Marivate, Vukosi},
  journal={Data in Brief},
  volume={47},
  pages={111567},
  year={2025},
  publisher={Elsevier},
  doi={10.1016/j.dib.2025.111567}
}

License

This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

For more information, please refer to the associated publication.