Propositional and Non-at-issue Content in Text Generation: Exploring the QUD–Perspective

基于讨论问题（Question under discussion， QUD）的语篇结构方法有助于对许多不同的语用现象进行简洁的分析，但迄今为止，这种方法在自然语言生成的研究中并未受到太多关注。我们想研究QUD方法在生成短路测试报告中的描述性和解释性强度。从解释到生成的角度，提出了关于假设量子点和量子点结构的正当性的几个新的计算和理论研究问题。为此，我们研究了建立话语关系、连接词和实现相应话语标记、句子聚合、评价副词的使用以及确定焦点的条件，因为这些内容确定和语言实现的任务原则上可以从相应的基于qud的话语结构理论中推导出来。我们开发了一个NLG系统作为概念验证，该系统可以根据数据库中的信息和来自文本的QUDs生成关于汽车和摩托车的短路测试报告。

Question under discussion (QUD)-based approaches to discourse structuring facilitate concise analyses of a bunch of different pragmatic phenomena but up to now, they did not receive much attention in research on natural language generation. We want to investigate the descriptive and explanatory strength of the QUD approach for the generation of short road test reports. Inverting the perspective from interpretation to generation raises several new computationally and theoretically motivated research questions concerning the justification of assumed QUDs and QUD structures.For this, we investigate the conditions for establishing discourse relations, connectives and realizing corresponding discourse markers, sentence aggregation, the use of evaluative adverbs, and determining the focus, since these tasks for content determination and linguistic realization can, in principle, be derived from corresponding QUD-based theories of discourse structuring.We develop an NLG system as proof-of-concept that generates short road test reports about cars and motorbikes from information in a database and QUDs derived from texts.