如何组合tachinesename(实体):分割和组合问题

Hongyan Jing, Radu Florian, Xiaoqiang Luo, Tong Zhang, Abraham Ittycheriah
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引用次数: 31

摘要

在构建中文命名实体识别系统时,必须处理某些特定于语言的问题,例如模型应该基于字符还是基于单词。虽然这个问题没有唯一的答案,但我们详细讨论了每种模型的优缺点,确定了分割中的问题,并提出了可能的解决方案,展示了我们的观察、分析和实验结果。本文的第二个主题是分类器组合。提出并描述了用于中文命名实体识别的四种分类器,并描述了组合它们的输出的各种方法。结果表明,分类器组合是提高系统性能的有效技术:在大型细粒度实体类型注释语料库上进行的实验显示,F-measure误差相对降低了10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HowtogetaChineseName(Entity): Segmentation and Combination Issues
When building a Chinese named entity recognition system, one must deal with certain language-specific issues such as whether the model should be based on characters or words. While there is no unique answer to this question, we discuss in detail advantages and disadvantages of each model, identify problems in segmentation and suggest possible solutions, presenting our observations, analysis, and experimental results. The second topic of this paper is classifier combination. We present and describe four classifiers for Chinese named entity recognition and describe various methods for combining their outputs. The results demonstrate that classifier combination is an effective technique of improving system performance: experiments over a large annotated corpus of fine-grained entity types exhibit a 10% relative reduction in F-measure error.
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