Xiaofan Yan, Jie Cheng, Ru Zhang, Jiahui Wei, Liandong Chen, Kai Cheng
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Chinese Short Text Entity Linking Model Based on PET
Existing Chinese short text entity link models are less, and the short text is limited and handled by the context missing and the processing noise. There is still a lot of space to improve the accuracy. This paper proposes a Chinese short text entity linking model, encoding the mention and entity representation of Pattern-Exploiting Training (PET), and learning the potential relationship between the entities in the knowledge base, based on contrastive learning. Our Chinese short text model experiments on Duel2.0 dataset and improves the result.
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