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.
- Automatic dataset construction
- Question answering dataset
- Under-resourced Language