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SEACrowd/ac_iquad
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Citation text from the card
@article{afa5bf8149d6406786539c1ea827087d,
title = "AC-IQuAD: Automatically Constructed Indonesian Question Answering Dataset by Leveraging Wikidata",
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.",
keywords = "Automatic dataset construction, Question answering dataset, Under-resourced Language",
author = "Kerenza Doxolodeo and Krisnadhi, {Adila Alfa}",
note = "Publisher Copyright: { extcopyright} 2024, The Author(s).",
year = "2024",
doi = "10.1007/s10579-023-09702-y",
language = "English",
journal = "Language Resources and Evaluation",
issn = "1574-020X",
publisher = "Springer Netherlands",
}
@article{lovenia2024seacrowd,
title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages},
author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jenn
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dataset_licence({ "id": "SEACrowd/ac_iquad" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0