计算机与现代化Issue(2)：69-74,6.DOI:10.3969/j.issn.1006-2475.2024.02.011
基于语义分割的嵌套命名实体识别方法
Nested Named Entity Recognition Based on Semantic Segmentation
摘要
Abstract
Named entity recognition aims to extract entities from an unstructured text,and a nested structure often exists be-tween entities.However,most of the previous studies only focused on the recognition of flat named entities while ignoring nested entities.Therefore,a nested named entity recognition method based on semantic segmentation is proposed,which describes the task of nested named entity recognition as a semantic segmentation task.First,we calculate the element similarity,cosine simi-larity and bilinear similarity between words and words.Then,the 3 similarity features are spliced as an image which will be input into the semantic segmentation model to obtain the relationship matrix between words and words.Finally,we extract nested entity from the relationship matrix.The experimental results show that the proposed method can effectively recognize nested entities,and the F1 value on the public nested named entity recognition dataset GENIA reaches 80.0%,which is superior to most existing nested entity recognition methods.关键词
嵌套命名实体识别/关系矩阵/语义分割/相关性特征Key words
nested named entity recognition/relation matrix/semantic segmentation/correlation feature分类
信息技术与安全科学引用本文复制引用
崔少国,胡光平..基于语义分割的嵌套命名实体识别方法[J].计算机与现代化,2024,(2):69-74,6.基金项目
国家自然科学基金资助项目(62003065) （62003065）
重庆市科技局自然基金资助项目(2022NSCQ-MSX2933,2022TFII-OFX0262,cstc2019jscx-mbdxX0061) （2022NSCQ-MSX2933,2022TFII-OFX0262,cstc2019jscx-mbdxX0061）
教育部人文社科规划基金资助项目(22YJA870005) （22YJA870005）
重庆市教委重点项目(KJZD-K202200510) （KJZD-K202200510）
重庆市社会科学规划项目(2022NDYB119) （2022NDYB119）
重庆师范大学人才基金项目(20XLB004) （20XLB004）
