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作 者:刘作国 陈笑蓉[1] Liu Zuoguo;Chen Xiaorong(College of Computer Science and Technology,Guizhou University,Guiyang,550025,China)
机构地区:[1]贵州大学计算机科学与技术学院
出 处:《南京大学学报(自然科学版)》2019年第6期1010-1019,共10页Journal of Nanjing University(Natural Science)
基 金:国家自然科学基金(61363028)
摘 要:近年来,实体挖掘技术已经成为文本信息处理领域的研究热点,有广泛的应用前景,但目前实体挖掘技术通常缺少句法层面的分析,很难从语句中准确抽取关键性词汇,并且抽取实体的过程容易忽略主客体的动作关联.针对这一问题,建立一个适用于汉语句法分析的论元关系模型.使用多值递归函数识别句型结构并划分句法功能语块,根据句型结构抽取动作的施体和受体,建立论元关系模型.多值递归函数的分析窗口涵盖整个语句,函数递归地探索整个解空间,获取全局最优解.此外,层次分解机制可以识别处理嵌套句和歧义句,能够抽取出更有价值的句法成分,对长语句和复杂语句有更好的适应能力.In recent years,the technology of entity extraction has become a hot research point in field of text information processing for its broad application prospect.Currently,the technology is usually lack of syntactic analyses so that it is not only hard to extract crucial words from sentences,but also easy to ignore action relations between subjects and objects during the period of extracting entities.To solve this problem,this paper establishes an Argument Relationship Model(ARM)which orients to Chinese syntactic analyses.Multivalued Recursive Functions(MRF)is taken into recognitions of sentence patterns and segment syntactic function chunks.Then senders and receptors of actions are extracted and ARM is established on the basis of sentence patterns.Analyzing window of MRF covers the whole sentence and it can explore the whole solution space recursively for its global optimal solution.What’s more,the Layer Decomposition Mechanism is useful for recognizing and processing nested or ambiguous sentences in order to extract more valuable syntactic components from long or complex sentences.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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