Datasets:
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---
task_categories:
- summarization
- feature-extraction
language:
- vi
pretty_name: Vietnamese NewsSapo Dataset
size_categories:
- 10M<n<100M
---
Vietnamese NewsSapo Dataset
The Vietnamese NewsSapo dataset was constructed to train sentence/passage embeddings. Our dataset is structured in a "title-abstract-contents" format, where each news article is represented by a tuple of (title, abstract, content). The content is the main text body of the article and has been processed to remove images, videos, and other non-textual elements. The dataset contains 31,728,183 triples.
To build this dataset, we followed a two-step process:
Step 1: Collect news data from 2021-11/2023. Combine with [Binhvq News Corpus](https://github.com/binhvq/news-corpus) to form a unified dataset.
Step 2: Extract title-sapo-content for each article.
### Please cite our manuscript if this dataset is used for your work
```
@article{duc2024towards,
title={Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models},
author={Nguyen Quang Duc, Le Hai Son, Nguyen Duc Nhan, Nguyen Dich Nhat Minh, Le Thanh Huong, Dinh Viet Sang},
journal={arXiv preprint arXiv:2403.01616},
year={2024}
}
``` |