@inproceedings{nguyen-huynh-2022-dangnt,
title = "{DANGNT}-{SGU} at {S}em{E}val-2022 Task 11: Using Pre-trained Language Model for Complex Named Entity Recognition",
author = "Nguyen, Dang and
Huynh, Huy Khac Nguyen",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.203/",
doi = "10.18653/v1/2022.semeval-1.203",
pages = "1483--1487",
abstract = "In this paper, we describe 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."
}
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%0 Conference Proceedings
%T DANGNT-SGU at SemEval-2022 Task 11: Using Pre-trained Language Model for Complex Named Entity Recognition
%A Nguyen, Dang
%A Huynh, Huy Khac Nguyen
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F nguyen-huynh-2022-dangnt
%X In this paper, we describe 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.
%R 10.18653/v1/2022.semeval-1.203
%U https://aclanthology.org/2022.semeval-1.203/
%U https://doi.org/10.18653/v1/2022.semeval-1.203
%P 1483-1487
Markdown (Informal)
[DANGNT-SGU at SemEval-2022 Task 11: Using Pre-trained Language Model for Complex Named Entity Recognition](https://aclanthology.org/2022.semeval-1.203/) (Nguyen & Huynh, SemEval 2022)
ACL