LanceBunag/BalitaNLP
A Filipino multi-modal language dataset for text+visual tasks. Consists of 351,755 Filipino news articles (w/ associated images) gathered from Filipino news outlets. Description Total # of articles: 351,755 80-10-10 split for training, validation, and testing. Dataset field descriptions: title - Article title body - Article body. Separated into paragraphs image - Article image website… See the full description on the dataset page: https://huggingface.co/datasets/LanceBunag/BalitaNLP.
A Filipino multi-modal language dataset for text+visual tasks. Consists of 351,755 Filipino news articles (w/ associated images) gathered from Filipino news outlets.
Description
Total # of articles: 351,755
80-10-10 split for training, validation, and testing.
Dataset field descriptions:
title - Article title
body - Article body. Separated into paragraphs
image - Article image
website - Name of the news outlet
category_group - Category grouped into 5 distinct classes. News, Sports, Entertainment, Crime, and Other
category - News category name given by the news outlet
date - Date published
author - Article author
url - URL of the article
img_url - URL of the article image
title_choice_first_paragraph - Opening paragraph of the article
title_choices - 4 possible titles, one of them being the true one
title_choice_gold_idx - Idx of the true title among the choicestitlechoice* fields are included to support the task of textual entailment — taking advantage of the "inverted pyramid" structure of news articles.
Dataset Usage
Two dataset configurations: default (includes images) and no-image (excludes images)
Using datasets library
default
from datasets import load_dataset
dset = load_dataset('LanceBunag/BalitaNLP', streaming=True) # streaming recommended due to size of dataset w/ imagesno-image
from datasets import load_dataset
dset = load_dataset('LanceBunag/BalitaNLP', 'no-image')Citation
Published in Buñag & Esquivel, 2023. If you are using BalitaNLP in your work, please cite the following:
@inproceedings{bunagtransformer,
author={Bunag, Kenrick Lance T and Esquivel, Rosanna A}
title={Transformer-Based Conditional Language Models to Generate Filipino News Articles},
year = {2023},
publisher = {IEOM Society International},
url = {https://ieomsociety.org/proceedings/2023manila/595.pdf},
booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management},
pages = {2231–2237},
numpages = {7},
location = {Manila, Philippines},
}