Few-shot Named Entity Recognition Method Based on Label Prompt and Gate Mechanism
Few-shot named entity recognition aims to achieve automatic recognition of named entities via a few sam-ples.Recently,the two-stage prototype network has achieved good results in few-shot named entity recognition tasks,but there are still problems of false positives in span detection and inaccurate prototypes in span classification.In response to the above problems,this paper proposes a few-shot named entity recognition model based on label prompts and gate mechanisms.Label prompt information is used to optimize sentence representation and reduce the occurrence of false positives in span detection.The gating module is introduced to fuse the label information and sample prototypes,so as to obtain a more accurate prototype representation in span classification.Experimental re-sults on multiple datasets show that the proposed method achieves an improvement of 10.63%in the F1 value.