| | --- |
| | 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} |
| | } |
| | ``` |
