TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya

arXiv:2404.17194v1 Announce Type: new
Abstract: The absence of explicitly tailored, accessible annotated datasets for educational purposes presents a notable obstacle for NLP tasks in languages with limited resources.This study initially explores the feasibility of using machine translation (MT) to convert an existing dataset into a Tigrinya dataset in SQuAD format. As a result, we present TIGQA, an expert annotated educational dataset consisting of 2.68K question-answer pairs covering 122 diverse topics such as climate, water, and traffic. These pairs are from …

abstract arxiv cs.cl dataset datasets educational expert format languages machine machine translation nlp question question answering resources study tasks translation type