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arXiv · 2504.21016

Nested Named-Entity Recognition on Vietnamese COVID-19: Dataset and Experiments

Ngoc C. Lê·Hai-Chung Nguyen-Phung·Thu-Huong Pham Thi·Hue Vu·Phuong-Thao Nguyen Thi·Thu-Thuy Tran·Hong-Nhung Le Thi·Thuy-Duong Nguyen-Thi·Thanh-Huy Nguyen
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Abstract

The COVID-19 pandemic caused great losses worldwide, efforts are taken place to prevent but many countries have failed. In Vietnam, the traceability, localization, and quarantine of people who contact with patients contribute to effective disease prevention. However, this is done by hand, and take a lot of work. In this research, we describe a named-entity recognition (NER) study that assists in the prevention of COVID-19 pandemic in Vietnam. We also present our manually annotated COVID-19 dataset with nested named entity recognition task for Vietnamese which be defined new entity types using for our system.

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Ngoc C. Lê, Hai-Chung Nguyen-Phung, Thu-Huong Pham Thi, Hue Vu, Phuong-Thao Nguyen Thi, Thu-Thuy Tran, Hong-Nhung Le Thi, Thuy-Duong Nguyen-Thi, Thanh-Huy Nguyen. 2025-04-21. Nested Named-Entity Recognition on Vietnamese COVID-19: Dataset and Experiments. https://arxiv.org/abs/2504.21016

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