PQuAD: A Persian Question Answering Dataset
Computation and Language
2023-02-22 v1 Information Retrieval
Machine Learning
Abstract
We present Persian Question Answering Dataset (PQuAD), a crowdsourced reading comprehension dataset on Persian Wikipedia articles. It includes 80,000 questions along with their answers, with 25% of the questions being adversarially unanswerable. We examine various properties of the dataset to show the diversity and the level of its difficulty as an MRC benchmark. By releasing this dataset, we aim to ease research on Persian reading comprehension and development of Persian question answering systems. Our experiments on different state-of-the-art pre-trained contextualized language models show 74.8% Exact Match (EM) and 87.6% F1-score that can be used as the baseline results for further research on Persian QA.
Keywords
Cite
@article{arxiv.2202.06219,
title = {PQuAD: A Persian Question Answering Dataset},
author = {Kasra Darvishi and Newsha Shahbodagh and Zahra Abbasiantaeb and Saeedeh Momtazi},
journal= {arXiv preprint arXiv:2202.06219},
year = {2023}
}