中文命名实体抽取的研究，存在分词、领域和方法三个方面的问题需要解决。
After summarizing and analyzing the state of the art on Chinese name entity extraction, we emphasize that three fundamental problems including word segmentation, domain, and method should be solved.
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.
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.
组织机构名等命名实体的识别是信息抽取、机器翻译等任务的重要基础。
The recognition of organization names is one of the fundamental tasks in Information Extraction and Machine Translation.
组织机构名等命名实体的识别是信息抽取、机器翻译等任务的重要基础。
The recognition of organization names is one of the fundamental tasks in Information Extraction and Machine Translation.
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