A Chinese Nested Named Entity Recognition Model for Chicken Disease Based on Multiple Fine-Grained Feature Fusion and Efficient Global Pointer

Extracting entities from large volumes of chicken epidemic texts is crucial for knowledge sharing, integration, and application. However, named entity recognition (NER) encounters significant challenges in this domain, particularly due to the prevalence of nested entities and domain-specific named e...

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מידע ביבליוגרפי

Principais autores:	Xiajun Wang, Cheng Peng, Qifeng Li, Qinyang Yu, Liqun Lin, Pingping Li, Ronghua Gao, Wenbiao Wu, Ruixiang Jiang, Ligen Yu, Luyu Ding, Lei Zhu
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2024-09-01
סדרה:	Applied Sciences
נושאים:	nested named entity recognition chicken disease multiple fine-grained feature fusion RoBERTa efficient global pointer
גישה מקוונת:	https://www.mdpi.com/2076-3417/14/18/8495
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