PhoNLP: A joint multi-task learning model for Vietnamese part-of-speech tagging, named entity recognition and dependency parsing

01/05/2021 ∙ by Linh The Nguyen, et al. ∙ 0

We present the first multi-task learning model – named PhoNLP – for joint Vietnamese part-of-speech tagging, named entity recognition and dependency parsing. Experiments on Vietnamese benchmark datasets show that PhoNLP produces state-of-the-art results, outperforming a single-task learning approach that fine-tunes the pre-trained Vietnamese language model PhoBERT (Nguyen and Nguyen, 2020) for each task independently. We publicly release PhoNLP as an open-source toolkit under the MIT License. We hope that PhoNLP can serve as a strong baseline and useful toolkit for future research and applications in Vietnamese NLP. Our PhoNLP is available at https://github.com/VinAIResearch/PhoNLP

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PhoNLP

PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing


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