@inproceedings{19f828e6386a4c5c88cb470ffaa7c431,
title = "NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model",
abstract = "This study describes the model design of the NCUEE-NLP system for the Chinese track of the SemEval-2022 MultiCoNER task. We use the BERT embedding for character representation and train the BiLSTM-CRF model to recognize complex named entities. A total of 21 teams participated in this track, with each team allowed a maximum of six submissions. Our best submission, with a macro-averaging F1-score of 0.7418, ranked the seventh position out of 21 teams.",
author = "Lee, {Lung Hao} and Lu, {Chien Huan} and Lin, {Tzu Mi}",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 16th International Workshop on Semantic Evaluation, SemEval 2022 ; Conference date: 14-07-2022 Through 15-07-2022",
year = "2022",
doi = "10.18653/v1/2022.semeval-1.220",
language = "English",
series = "SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "1597--1602",
editor = "Guy Emerson and Natalie Schluter and Gabriel Stanovsky and Ritesh Kumar and Alexis Palmer and Nathan Schneider and Siddharth Singh and Shyam Ratan",
booktitle = "SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop",
address = "美國",
}