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A Pr/T-Net model for context-free language parsing

机译:用于上下文无关语言解析的Pr / T-Net模型

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This paper presents a Context-Free Grammar-Predicate/Transition-Net (CFG-Pr/T-Net) model for the parsing of context-free language. The places are defined to represent the states of the parsing process. The conditions and actions carried by the transitions are defined such that non-terminal symbols being processed can be rewritten and the derivation can be made to grow. Data structures, as the personalities of the token, are defined such that the growing derivation can be stored in the token. An application example was examined and the result shows that the Pr/T-Net model can do syntactic parsing successfully. The CFG-Pr/T-Net overcomes the limitation of pushdown automata, which only judged whether a string belonged to a given context free language, but were not able to answer the question concerning syntactic structure.
机译:本文提出了一种上下文无关语法-谓词/过渡网(CFG-Pr / T-Net)模型,用于解析上下文无关语言。定义这些位置以表示解析过程的状态。定义转换所携带的条件和动作,以便可以重写正在处理的非终端符号,并且可以使派生增长。定义数据结构作为令牌的个性,以便可以将增长的派生存储在令牌中。研究了一个应用实例,结果表明Pr / T-Net模型可以成功地进行语法分析。 CFG-Pr / T-Net克服了下推自动机的局限性,后者仅判断字符串是否属于给定的上下文无关语言,而无法回答有关语法结构的问题。

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