TY - JOUR
T1 - AC-IQuAD
T2 - Automatically Constructed Indonesian Question Answering Dataset by Leveraging Wikidata
AU - Doxolodeo, Kerenza
AU - Krisnadhi, Adila Alfa
N1 - Publisher Copyright:
© 2024, The Author(s).
PY - 2024
Y1 - 2024
N2 - Constructing a question-answering dataset can be prohibitively expensive, making it difficult for researchers to make one for an under-resourced language, such as Indonesian. We create a novel Indonesian Question Answering dataset that is produced automatically end-to-end. The process uses Context Free Grammar, the Wikipedia Indonesian Corpus, and the concept of the proxy model. The dataset consists of 134 thousand simple questions and 60 thousand complex questions. It achieved competitive grammatical and model accuracy compared to the translated dataset but suffers from some issues due to resource constraints.
AB - Constructing a question-answering dataset can be prohibitively expensive, making it difficult for researchers to make one for an under-resourced language, such as Indonesian. We create a novel Indonesian Question Answering dataset that is produced automatically end-to-end. The process uses Context Free Grammar, the Wikipedia Indonesian Corpus, and the concept of the proxy model. The dataset consists of 134 thousand simple questions and 60 thousand complex questions. It achieved competitive grammatical and model accuracy compared to the translated dataset but suffers from some issues due to resource constraints.
KW - Automatic dataset construction
KW - Question answering dataset
KW - Under-resourced Language
UR - http://www.scopus.com/inward/record.url?scp=85181237467&partnerID=8YFLogxK
U2 - 10.1007/s10579-023-09702-y
DO - 10.1007/s10579-023-09702-y
M3 - Article
AN - SCOPUS:85181237467
SN - 1574-020X
JO - Language Resources and Evaluation
JF - Language Resources and Evaluation
ER -