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Bridging the Gap Between Formal Languages and Natural Languages with Zippers

机译:用拉链弥合形式语言与自然语言之间的鸿沟

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The Semantic Web is founded on a number of Formal Languages (FL) whose benefits are precision, lack of ambiguity, and ability to automate reasoning tasks such as inference or query answering. This however poses the challenge of mediation between machines and users because the latter generally prefer Natural Languages (NL) for accessing and authoring knowledge. In this paper, we introduce the N<A>F design pattern based on Abstract Syntax Trees (AST), Huet's zippers and Montague grammars to zip together a natural language and a formal language. Unlike question answering, translation does not go from NL to FL, but as symbol N<A>F suggests, from ASTs (A) of an intermediate language to both NL (N<A) and FL (A>F). ASTs are built interactively and incrementally through a user-machine dialog where the user only sees NL, and the machine only sees FL.
机译:语义网建立在许多形式语言(FL)的基础上,其优点是精度高,缺乏歧义性以及能够自动执行诸如推理或查询回答之类的推理任务的能力。但是,这给机器和用户之间的调解带来了挑战,因为后者通常更喜欢自然语言(NL)来访问和创作知识。在本文中,我们介绍了基于抽象语法树(AST),Huet的拉链和Montague语法的N <A> F设计模式,以将自然语言和形式语言压缩在一起。与问题答案不同,翻译不是从NL到FL,而是从符号N <A> F暗示,从中间语言的AST(A)到NL(N <A)和FL(A> F)。 AST是通过用户-机器对话框以交互方式和增量方式构建的,在该对话框中,用户仅看到NL,而机器仅看到FL。

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