Chinese Named Entity Identification Using Class-based Language Model
Chinese Named Entity Identification Using Class-based Language Model
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DOI：
10.3115/1072228.1072240
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发表时间：
2002-08
期刊：
影响因子：
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通讯作者：
Jian Sun-;Jianfeng Gao;Lei Zhang;M. Zhou;C. Huang
中科院分区：
文献类型：
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作者：
Jian Sun-;Jianfeng Gao;Lei Zhang;M. Zhou;C. Huang
本文研究了基于统计语言模型的中文命名实体识别问题。在这项研究中，分词和NE识别已被集成到一个统一的框架，由几个基于类的语言模型。我们还采用了层次结构的LM之一，使嵌套的实体在组织名称可以识别。在大型测试集上的评估显示出一致的改进。我们的实验进一步证明了与语言启发式信息，基于缓存的模型和NE缩写识别无缝集成后的改进。
We consider here the problem of Chinese named entity (NE) identification using statistical language model(LM). In this research, word segmentation and NE identification have been integrated into a unified framework that consists of several class-based language models. We also adopt a hierarchical structure for one of the LMs so that the nested entities in organization names can be identified. The evaluation on a large test set shows consistent improvements. Our experiments further demonstrate the improvement after seamlessly integrating with linguistic heuristic information, cache-based model and NE abbreviation identification.