AC-IQuAD: Automatically Constructed Indonesian Question Answering Dataset by Leveraging Wikidata

Kerenza Doxolodeo, Adila Alfa Krisnadhi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
JournalLanguage Resources and Evaluation
DOIs
Publication statusAccepted/In press - 2024

Keywords

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

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