Abstract: At present，the Chinese text processing in English-Chinese parallel corpus，more confined to only use monolingual analysis results，without sufficient use bilingual resources.Structural relation of contemporary Chinese v+n sequence is regarded as the research object，and the parallel processing algorithm is designed for recognizing v+n structural relation in English-Chinese parallel corpus.At first，this paper utilizes various form single language resources to extract the restriction rules of verb and noun that having different structural relations.And then judges v+n structural relation type separately according to translation of Chinese noun and verb，and context template in parallel English text.The experiment proves，in PCCE1000 which having been word-segmented and POS-tagged，F value that using single language resources to process v+n is 72.14%，and further utilizing the Chinese-English dictionary and English translation information，F value has reached 88.81%，having improved by 16.67 percentage points.

Key words: parallel corpus, collocation, phrase analysis, automatic recognition, Chinese information processing

摘要： 目前，在英汉平行语料中，对汉语文本的深加工多局限于只利用单语分析的成果，没有充分利用双语资源。以现代汉语v+n序列的结构关系为研究对象，设计出在英汉平行语料中识别v+n结构关系的平行处理算法：首先利用各种单语资源，提取出构成不同结构关系的动词和名词相互间的制约规则，再分别依据v+n中汉语名词、动词的语义在英语译文中的具体形式及上下文模板来判断v+n的结构关系类型。实验证明，在自动分词和词性标注的PCCE1000文本中，v+n单语处理的F值为72.14%，而进一步利用汉英词典和英语译文信息，F值到达了88.81%，提高了16.67个百分点。

关键词: 平行语料, 词语搭配, 短语分析, 自动识别, 中文信息处理