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.

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本文提出了一种新颖的方法，综合利用音译和网络挖掘来提高命名实体翻译的效果。

This paper presents a novel approach to improve the named entity translation by combining transliteration with web mining.

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命名实体识别是生物医学文献文本挖掘重要的第一步。

Named entity recognition is the first key stage of text mining in the exploding biomedical literature.

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