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

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

電機工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

2 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 2022 → 15 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	14/07/22 → 15/07/22

中文醫療健康照護知識庫建置與應用(3/3)
Lee, L.
1/05/21 → 31/07/22
研究計畫: Research

引用此

Lee, L. H., Lu, C. H., & Lin, T. M. (2022). NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model. 於 G. Emerson, N. Schluter, G. Stanovsky, R. Kumar, A. Palmer, N. Schneider, S. Singh, & S. Ratan (編輯), SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (頁 1597-1602). (SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop). Association for Computational Linguistics (ACL).

Lee, Lung Hao ; Lu, Chien Huan ; Lin, Tzu Mi. / NCUEE-NLP at SemEval-2022 Task 11 : Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model. 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. Association for Computational Linguistics (ACL), 2022. 頁 1597-1602 (SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop).

@inproceedings{5fbaa6d01ab84baab9f5d0b75496783c,

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",

language = "???core.languages.en_GB???",

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",

}

Lee, LH, Lu, CH & Lin, TM 2022, NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model. 於 G Emerson, N Schluter, G Stanovsky, R Kumar, A Palmer, N Schneider, S Singh & S Ratan (編輯), SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop. SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop, Association for Computational Linguistics (ACL), 頁 1597-1602, 16th International Workshop on Semantic Evaluation, SemEval 2022, Seattle, United States, 14/07/22.

NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model. / Lee, Lung Hao; Lu, Chien Huan; Lin, Tzu Mi.
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. Association for Computational Linguistics (ACL), 2022. p. 1597-1602 (SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - NCUEE-NLP at SemEval-2022 Task 11

T2 - 16th International Workshop on Semantic Evaluation, SemEval 2022

AU - Lee, Lung Hao

AU - Lu, Chien Huan

AU - Lin, Tzu Mi

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85137586190&partnerID=8YFLogxK

M3 - 會議論文篇章

AN - SCOPUS:85137586190

T3 - SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

SP - 1597

EP - 1602

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

A2 - Emerson, Guy

A2 - Schluter, Natalie

A2 - Stanovsky, Gabriel

A2 - Kumar, Ritesh

A2 - Palmer, Alexis

A2 - Schneider, Nathan

A2 - Singh, Siddharth

A2 - Ratan, Shyam

PB - Association for Computational Linguistics (ACL)

Y2 - 14 July 2022 through 15 July 2022

ER -

Lee LH, Lu CH, Lin TM. NCUEE-NLP at SemEval-2022 Task 11: Chinese Named Entity Recognition Using the BERT-BiLSTM-CRF Model. 於 Emerson G, Schluter N, Stanovsky G, Kumar R, Palmer A, Schneider N, Singh S, Ratan S, 編輯, SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2022. p. 1597-1602. (SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop).

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

摘要

出版系列

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指紋

專案

中文醫療健康照護知識庫建置與應用(3/3)

引用此