Open Korean Corpora: A Practical Report on Language Resources
Researchers have published an updated survey cataloging open Korean language corpora for natural language processing, arguing that Korean is underrepresented in NLP not solely due to a lack of data but due to poor curation and advertisement of existing resources. The paper, originally presented at NLP-OSS at EMNLP 2020, has been updated twice — most recently in June 2026 — adding new datasets and analyses. It matters because it provides a practical roadmap for improving dataset discoverability for Korean and offers a model for how less-resourced languages can better promote their available resources.
A research paper titled 'Open Korean Corpora: A Practical Report' surveys and reviews publicly available Korean language datasets for NLP tasks, challenging the widespread characterization of Korean as a strictly low-resource language. The authors argue that while resource scarcity is a real concern, much of the problem stems from inadequate curation and visibility of existing corpora rather than an absolute absence of data. The paper organizes resources at the institution level before cataloging datasets by task type, providing a structured reference for researchers. Originally published at the NLP-OSS workshop at EMNLP 2020, the paper has undergone two major updates — in May 2023 and June 2026 — expanding its dataset listings and adding new analyses. The authors also propose guidelines for how open-source dataset construction and release practices should be structured for less-resourced languages to better support the research community.
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- arXiv cs.CLCenter
Open Korean Corpora: A Practical Report
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