NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model

Lung Hao Lee, Chien Huan Lu, Tzu Mi Lin

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

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.

原文???core.languages.en_GB???
主出版物標題SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
編輯Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
發行者Association for Computational Linguistics (ACL)
頁面1597-1602
頁數6
ISBN(電子)9781955917803
出版狀態已出版 - 2022
事件16th International Workshop on Semantic Evaluation, SemEval 2022 - Seattle, United States
持續時間: 14 7月 202215 7月 2022

出版系列

名字SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

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???event.eventtypes.event.conference???16th International Workshop on Semantic Evaluation, SemEval 2022
國家/地區United States
城市Seattle
期間14/07/2215/07/22

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