DANGNT-SGU at SemEval-2022 Task 11: Using Pre-trained Language Model for Complex Named Entity Recognition
Dang Khoa Nguyen, Huy Khac Nguyen Huynh · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
This paper describes a system that we built to participate in the SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, specifically the track Mono-lingual in English.To construct this system, we used Pre-trained Language Models (PLMs).Especially, the Pre-trained Model base on BERT is applied for the task of recognizing named entities by fine-tuning method.We performed the evaluation on two test datasets of the shared task: the Practice Phase and the Evaluation Phase of the competition.