Open Korean Corpora: A Practical Report on Language Resources
Researchers have curated and reviewed a comprehensive list of Korean language corpora, challenging the perception that Korean is a low-resource language by documenting available datasets and institutional resources. The work distinguishes between the actual scarcity of Korean NLP resources and the problem of inadequate visibility and curation of existing materials. The findings provide guidance for how less-resourced languages should approach open-source dataset construction and release to better support research.
A research paper published at NLP-OSS@EMNLP2020 and updated through June 2026 examines the state of Korean language corpora available to the research community. While Korean is commonly labeled a low-resource language, the authors argue this characterization is partly misleading—the real issue is that available resources are not well-advertised or systematically curated. The paper reviews institution-level resource development efforts and catalogs current open datasets across different NLP task types. Based on this analysis, the authors propose best practices for how languages with limited resources should structure and release open-source datasets to maximize research accessibility and impact. The work has been iteratively updated to include new datasets and analyses, with the most recent version significantly expanded from the original publication.
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- arXiv cs.CLCenter
Open Korean Corpora: A Practical Report
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