实验证明srv算法用于命名实体关系的抽取是成功和有效的。
The experiment demonstrates that SRV is successful and effective for the named entity relation extraction.
图1显示一个包含用于已命名实体识别、语法分析和关系探测的注释器的分析引擎。
Figure 1 shows an analysis engine containing annotators for named entity recognition, grammatical parsing, and relationship detection.
关系抽取是文本挖掘的一项重要研究内容，它能够反映命名实体之间的关系，有助于发现隐含在大量数据和文本中的知识。
Relation extraction is an important task in text mining, it can reflect the relationship between the named entities and is helpful to find implicit knowledge in the substantial data and text.
通过以上两种方法，使命名实体之间关系抽取结果的性能大大提高。
By doing these, the performance of named entity relation extraction was enhanced greatly.
本文实现了命名实体识别和实体关系提取。
Web information extraction includes named entity recognition and entity relationship extraction.
本文实现了命名实体识别和实体关系提取。
Web information extraction includes named entity recognition and entity relationship extraction.
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