摘要
信息抽取是自然语言处理中的重要部分,也是构建问答系统、知识图谱的重要基础.随着深度学习技术的发展,越来越多的新技术被应用到信息抽取.先介绍了信息抽取技术的产生和主要任务,再详细阐述了信息抽取技术的发展,然后给出了一个基于BERT的信息抽取模型,最后讨论了信息抽取技术面临的一些问题和研究方向.
Information extraction is an important part of natural language processing,and it is also an important foundation for constructing question-answering systems and knowledge graphs.With the development of deep learning technology,more and more new technologies are applied to information extraction.This paper first introduces the emergence and main tasks of information extraction technology,and then expounds the development of information extraction technology in detail,and then gives an information extraction model based on Bert.Finally,some problems and research directions of information extraction technology are discussed.
作者
肖明
曾莉
XIAO Ming;ZENG Li(School of Computer Science and Engineering,Southwest Minzu University,Chengdu 610041,China;School of Mathematics,Southwest Minzu University,Chengdu 610041,China)
出处
《西南民族大学学报（自然科学版）》
CAS
2021年第6期633-639,共7页
Journal of Southwest Minzu University(Natural Science Edition)
基金
西南民族大学中央高校基本科研业务费专项资金项目资助(2014NZYQN57)。
关键词
自然语言处理
信息抽取
关系抽取
深度学习
BERT
natural language processing
information extraction
relationship extraction
deep learning
BERT
