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CHOOSING RHETORICAL STRUCTURES TO PLAN INSTRUCTIONAL TEXTS

机译:选择修辞结构来计划教学文本

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This paper discusses a fundamental problem in natural language generation: how to organize the content of a text in a coherent and natural way. In this research, we set out to determine the semantic content and the rhetorical structure of texts and to develop heuristics to perform this process automatically within a text generation framework. The study was performed on a specific language and textual genre: French instructional texts. From a corpus analysis of these texts, we determined nine senses typically communicated in instructional texts and seven rhetorical relations used to present these senses. From this analysis, we then developed a set of presentation heuristics that determine how the senses to be communicated should be organized rhetorically in order to create a coherent and natural text. The heuristics are based on five types of constraints: conceptual, semantic, rhetorical, pragmatic, and intentional constraints. To verify the heuristics, we developed the SPIN natural language generation system, which performs all steps of text generation but focuses on the determination of the content and the rhetorical structure of the text.
机译:本文讨论自然语言生成中的一个基本问题:如何以连贯和自然的方式组织文本的内容。在这项研究中,我们着手确定文本的语义内容和修辞结构,并开发启发式方法以在文本生成框架内自动执行此过程。这项研究是针对特定的语言和文本类型进行的:法语教学文本。通过对这些文本的语料库分析,我们确定了通常在教学文本中传达的九种感觉,以及用于表达这些感觉的七种修辞关系。通过此分析,我们然后开发了一组演示启发法,这些启发法确定了应如何用言语来组织要传达的感官,以便创建连贯而自然的文本。启发式方法基于五种约束:概念,语义,修辞,语用和故意约束。为了验证启发式方法,我们开发了SPIN自然语言生成系统,该系统执行文本生成的所有步骤,但着重于确定文本的内容和修辞结构。

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