Abstract:

Named entity recognition is an important basic task in information extraction, machine translation, question answering system and other natural language processing technologies. In recent years, named entity recognition based on deep learning has become a hot topic for researchers. In order to analyze the progress and future development trend of named entity recognition based on deep learning, this paper gives an overview of the current methods of named entity recognition including the methods based on convolutional neural network, cyclic neural network, transformer model and some other methods, and studies and compares the four methods in detail. This paper also introduces the application fields of named entity recognition and the data sets and evaluation methods involved. Finally, the future research directions are prospected.

Key words: natural language processing, named entity recognition, deep learning

摘要：

命名实体识别技术是信息抽取、机器翻译、问答系统等多种自然语言处理技术中一项重要的基本任务。近年来，基于深度学习的命名实体识别技术成为一大研究热点。为了方便研究者们了解基于深度学习的命名实体识别研究进展及未来发展趋势，对当前基于卷积神经网络、循环神经网络、transformer模型以及其他一些命名实体识别方法展开综述性介绍，对四类方法进行了深入分析和对比。同时对命名实体识别应用领域以及所涉及到的数据集和评测方法进行了介绍，并对未来的研究方向进行了展望。

关键词: 自然语言处理, 命名实体识别, 深度学习