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Automatic Entity Relation Extraction Based on Conditional Random Fields

机译:基于条件随机字段的自动实体关系提取

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Entity Relation Extraction (RE) is one of the important research fields in Information Extraction, we regard RE as a classification problem in this paper, This paper presents a novel approach, Conditional Random Fields (CRFs)-based machine learning is used to extract entity relation between entities from Chinese texts, ten features have been designed for entity relation extraction, which includes morphology, grammar and semantic feature. Experimental results show that the new approach achieve an improved performance on corpus for Chinese entity relation extraction.
机译:实体关系提取(RE)是信息提取中的重要研究领域之一,我们认为RE作为分类问题,本文提出了一种新的方法,条件随机字段(CRF)基于机器学习用于提取实体来自中文文本的实体之间的关系,为实体关系提取设计了十种功能,包括形态,语法和语义特征。实验结果表明,新方法实现了中国实体关系提取语料库的性能。

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