language:
- ha
license: apache-2.0
task_categories:
- summarization
Dataset Card for Dataset Name
Hausa text-extractive ATS evaluation dataset. The dataset comprises 113 Hausa news articles from different genres, including sports, religion, politics, and culture. For each news article, there are two corresponding, manually generated gold standard summaries, whose lengths are 20% of the original article.
- Curated by: Abdulkadir Abubakar Bichi
- Language(s) (NLP): Hausa
- Repository: (https://doi.org/10.1371/journal.pone.0285376.s001)
- Paper: [More Information Needed]
Source Data
The dataset comprises 113 Hausa news articles from different genres, including sports, religion, politics, and culture.
Data Architecture
Each entry in the dataset contains the following fields:
id: a unique string identifier for each example. article: a list[string] field representing the original news article. refrence1: a list[string] field representing the professionally gold summary of the article.
Usage
The extractive dataset can be used to tevaluate models for extractive text summarization tasks on Hausa Language single documents. It allows models to learn to predict which sentences from an original text contribute to a summary. The 'reference1 and reference2' field can serve as a basis for comparison, helping to assess how well the selected sentences cover the key points in the article.
Who are the annotators?
Abdulqahar M. Abubakar and Abdulaziz Aminu
Citation [optional]
BibTeX:
@article{Bichi2023GraphbasedET, title={Graph-based extractive text summarization method for Hausa text}, author={Abdulkadir Abubakar Bichi and Ruhaidah Samsudin and Rohayanti Hassan and Layla Rasheed Abdallah Hasan and Abubakar Ado Rogo}, journal={PLOS ONE}, year={2023}, volume={18}, url={https://api.semanticscholar.org/CorpusID:258587667} }
APA:
[Bichi, A.A., Samsudin, R., Hassan, R., Hasan, L.R., & Ado Rogo, A. (2023). Graph-based extractive text summarization method for Hausa text. PLOS ONE, 18.]