Intelligent mining method of typi-cal semantic elements of aircraft assembly instruction is proposed to better achieve the extraction, organization and reuse of the elements. Standardized partition of statement structure is realized at the natural language level through preprocessing the data elements of aircraft assembly in-structions and these instructions are divided into semantic elements of typical instructions, standardized assembly instruction statements and typical instruction templates by analyzing semantic granularities. Based on Hidden Markov model, chunk labeling of assembly instructions is realized via a deep semantic concept analysis of these instructions under the guidance of the idea of chunk parsing. The intel-ligent mining of typical operational semantic elements of assembly instructions is completed by adopting the method of Apriori.%为了更好地实现对飞机装配指令典型语义元素的提取、组织、重用，提出了飞机装配指令典型语义元素智能挖掘方法。对飞机装配指令数据元素进行预处理，实现自然语言层面的语句结构标准化划分，通过对语义粒度的分析，将装配指令划分为典型指令语义元素、标准化装配指令语句、典型指令模板；采用语块分析理念对装配指令进行深层次的语义概念剖析，基于隐马尔可夫模型（Hidden Markov Model，HMM），实现对装配指令的语块标注。进一步采用Apriori方法，完成对装配指令典型操作语义元素的智能挖掘。
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