Luwidji/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 choices

title_choice_* 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/ images

no-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},
}