北京大学学报（自然科学版）2024，Vol.60Issue(3)：413-421,9.DOI:10.13209/j.0479-8023.2024.036
基于标签语义信息感知的少样本命名实体识别方法
Few-shot Named Entity Recognition Method Based on Semantic Information Awareness of Labels
摘要
Abstract
Among various approaches of few-shot named entity recognition(NER),two-stage models based on prototype networks are widely used.However,these methods can not fully utilize the semantic information in entity labels and overly relies on entity type prototype vectors in distance calculation,resulting in poor generalization ability of the model.To address these issues,this paper proposes a few-shot named entity recognition method based on label semantic information awareness.This method consists of a two-stage process:entity span detection and entity type classification.When constructing entity type prototype vectors,the semantic information associated with the corresponding entity types is considered and fused with the prototype vectors through a dimension transformation layer.During the entity recognition of new samples,entity type positive and negative samples are combined with entity type prototype vectors to form entity type triplets,and the samples are classified based on the distance to the triplets.Experimental results on multiple datasets demonstrate that the proposed model significantly outperforms previous models.关键词
少样本命名实体识别/标签语义信息感知/实体类型三元组/原型网络Key words
few-shot named entity recognition(NER)/semantic information awareness of labels/entity type triplet/prototypical network引用本文复制引用
张越,王长征,苏雪峰,闫智超,张广军,邵文远,李茹..基于标签语义信息感知的少样本命名实体识别方法[J].北京大学学报（自然科学版）,2024,60(3):413-421,9.基金项目
山西省重点研发计划(202102020101008)、山西省科技合作交流专项(202204041101016)和山西省 1331工程项目资助 （202102020101008）
