Few-shot named entity recognition framework for forestry science metadata extraction

Fan, Yuquan; Xiao, Hong; Wang, Min; Wang, Junchi; Jiang, Wenchao; Zhu, Chang

doi:10.1007/s12652-023-04740-4

J Ambient Intell Human Comput

2024

DOI: 10.1007/s12652-023-04740-4

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Few-shot named entity recognition framework for forestry science metadata extraction

Yuquan Fan,

Hong Xiao,

Min Wang

et al.

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DABC: A Named Entity Recognition Method Incorporating Attention Mechanisms

Leng,

Li,

Bao

et al. 2024

Mathematics

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Regarding the existing models for feature extraction of complex similar entities, there are problems in the utilization of relative position information and the ability of key feature extraction. The distinctiveness of Chinese named entity recognition compared to English lies in the absence of space delimiters, significant polysemy and homonymy of characters, diverse and common names, and a greater reliance on complex contextual and linguistic structures. An entity recognition method based on DeBERTa-Attention-BiLSTM-CRF (DABC) is proposed. Firstly, the feature extraction capability of the DeBERTa model is utilized to extract the data features; then, the attention mechanism is introduced to further enhance the extracted features; finally, BiLSTM is utilized to further capture the long-distance dependencies in the text and obtain the predicted sequences through the CRF layer, and then the entities in the text are identified. The proposed model is applied to the dataset for validation. The experiments show that the precision (P) of the proposed DABC model on the dataset reaches 88.167%, the recall (R) reaches 83.121%, and the F1 value reaches 85.024%. Compared with other models, the F1 value improves by 3∼5%, and the superiority of the model is verified. In the future, it can be extended and applied to recognize complex entities in more fields.

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DABC: A Named Entity Recognition Method Incorporating Attention Mechanisms

Leng,

Li,

Bao

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

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Few-shot named entity recognition framework for forestry science metadata extraction

Cited by 1 publication

References 17 publications

DABC: A Named Entity Recognition Method Incorporating Attention Mechanisms

DABC: A Named Entity Recognition Method Incorporating Attention Mechanisms

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