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Mining Knowledge in Storytelling Systems for Narrative Generation

机译:在叙事系统中挖掘知识以产生叙事

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Storytelling systems are computational systems designed to tell stories. Every story generation system defines its specific knowledge representation for supporting the storytelling process. Thus, there is a shared need amongst all the systems: the knowledge must be expressed unambiguously to avoid inconsistencies. However, when trying to make a comparative assessment between the storytelling systems, there is not a common way for expressing this knowledge. That is when a form of expression that covers the different aspects of the knowledge representations becomes necessary. A suitable solution is the use of a Controlled Natural Language (CNL) which is a good half-way point between natural and formal languages. A CNL can be used as a common medium of expression for this heterogeneous set of systems. This paper proposes the use of Controlled Natural Language for expressing every storytelling system knowledge as a collection of natural language sentences. In this respect, an initial grammar for a CNL is proposed, focusing on certain aspects of this knowledge.
机译:讲故事系统是旨在讲故事的计算系统。每个故事生成系统都会定义其特定的知识表示形式,以支持故事讲述过程。因此,所有系统之间都有共同的需求:必须明确表达知识以避免不一致。但是,当试图在故事系统之间进行比较评估时,没有表达这种知识的通用方法。那就是当一种涵盖知识表示的不同方面的表达形式变得必要时。合适的解决方案是使用受控自然语言(CNL),这是自然语言和形式语言之间的良好过渡。 CNL可用作此异构系统集的通用表达介质。本文提出使用受控自然语言来表达每个讲故事的系统知识,作为自然语言句子的集合。在这方面,提出了CNL的初始语法,重点是该知识的某些方面。

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