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中文摘要：
针对开放文本中中文实体关系抽取的一词多义问题，提出一种基于实体消歧的中文实体关系抽取方法。首先，从知网中挖掘出具有潜在语义关系的实体对，并利用贝叶斯分类的语义消歧方法实现从知网到维基百科的实体映射，以获取高质量的关系实例；然后，根据这些关系实例抽取出其对应文本中共现的句子实例，构建基本的抽取模式；最后通过模式合并的方法生成新模式，再使用新模式来抽取新实例。实验结果表明，该方法与没有进行语义消歧和模式合并的方法相比准确率有所提高。
英文摘要：
To solve the polysemy problem in Chinese Entity Relation Extraction in open text,a Chinese entity relation extraction method based on entity disambiguation was proposed.First,mining entity relation pairs from HowNet,and the entities were mapped from HowNet to Wikipedia by using disambiguation method based on Bayesian classification so as to obtain high-quality relationship instance;Then,extracting the sentence instances in the corresponding context with these relation instances,to construct a basic extraction pattern;Finally,extracting new cases use the new pattern.The experimental results showed that the accuracy of the proposed method was higher than the methods without semantic dis-ambiguation and pattern merging.
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