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

arXiv: https://arxiv.org/abs/2504.21016 · HTML: https://mlsanity.com/paper/2504.21016/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 21 references that are in the map.
- First posted on arXiv 21 Apr 2025.

## Builds on (most cited first, 14 of 14)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://mlsanity.com/paper/1904.01038/) (2019)
- [Bidirectional LSTM-CRF Models for Sequence Tagging](https://mlsanity.com/paper/1508.01991/) (2015)
- [PhoBERT: Pre-trained language models for Vietnamese](https://mlsanity.com/paper/2003.00744/) (2020)
- [Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing](https://mlsanity.com/paper/2101.03289/) (2021)
- [A large-scale COVID-19 Twitter chatter dataset for open scientific research -- an international collaboration](https://mlsanity.com/paper/2004.03688/) (2020)
- [Exploring Cross-sentence Contexts for Named Entity Recognition with BERT](https://mlsanity.com/paper/2006.01563/) (2020)
- [Automatic Text Summarization of COVID-19 Medical Research Articles using BERT and GPT-2](https://mlsanity.com/paper/2006.01997/) (2020)
- [A Fast and Accurate Vietnamese Word Segmenter](https://mlsanity.com/paper/1709.06307/) (2017)
- [COVID-19 Named Entity Recognition for Vietnamese](https://mlsanity.com/paper/2104.03879/) (2021)
- [Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo](https://mlsanity.com/paper/2005.09174/) (2020)
- [Improving Clinical Document Understanding on COVID-19 Research with Spark NLP](https://mlsanity.com/paper/2012.04005/) (2020)
- [A Feature-Based Model for Nested Named-Entity Recognition at VLSP-2018 NER Evaluation Campaign](https://mlsanity.com/paper/1803.08463/) (2018)

## Abstract (arXiv)

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.