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---
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
    dtype: string
  splits:
  - name: train
    num_bytes: 57867100
    num_examples: 1521
  - name: validation
    num_bytes: 10985252
    num_examples: 299
  - name: test
    num_bytes: 11291457
    num_examples: 298
  download_size: 42168935
  dataset_size: 80143809
- config_name: without_summaries
  features:
  - name: id
    dtype: string
  - name: type
    dtype: string
  - name: year
    dtype: string
  - name: input
    dtype: string
  splits:
  - name: all_data
    num_bytes: 55925930
    num_examples: 2053
  download_size: 29653319
  dataset_size: 55925930
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](https://huggingface.co/datasets/dsfsi/zasca-sum)

To load the dataset using the Hugging Face `datasets` library:


```python
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:


```bibtex
@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)](https://creativecommons.org/licenses/by-sa/4.0/) license.


---

For more information, please refer to the [associated publication](https://doi.org/10.1016/j.dib.2025.111567).

---