构建跨文本类型的道德化话语语料库，分析道德诉求的表达机制。
The Moralization Corpus: Frame-Based Annotation and Analysis of Moralizing Speech Acts across Diverse Text Genres
- 基于框架的标注体系，捕捉道德价值、诉求与对话主体三要素。
- 多类型德语文本中识别出高主观性与强语境依赖的道德化表达。
- 适合研究伦理话语、人机交互中的道德推理及批判性语言分析者。
道德化——通过诉诸道德价值来为立场或要求辩护的论证——是一种尚未充分探索的说服性沟通形式。本文提出道德化语料库（The Moralization Corpus），一个跨多种文本类型的新型数据集，旨在分析道德价值在论辩话语中如何被策略性使用。道德化具有语用复杂性和隐含性，对人工标注和自然语言处理系统均构成挑战。我们设计了一种基于框架的标注方案，捕捉道德化的核心要素：道德价值、诉求及话语主角，并将其应用于包括政治辩论、新闻报道和网络讨论在内的多样化德语文本。该语料库支持在不同传播形式与领域中进行细粒度的道德化语言分析。我们进一步评估了多个大语言模型（LLMs）在不同提示条件下的道德化检测与成分提取表现，并与人工标注结果对比，以探究自动与手动分析道德化的难点。结果显示，详细提示指令的效果优于少样本或解释性提示，且道德化仍是高度主观和依赖语境的任务。我们已公开所有数据、标注指南与代码，以促进未来关于道德话语与道德推理的跨学科研究。
原文摘要 · Abstract (English)
Moralizations - arguments that invoke moral values to justify demands or positions - are a yet underexplored form of persuasive communication. We present the Moralization Corpus, a novel multi-genre dataset designed to analyze how moral values are strategically used in argumentative discourse. Moralizations are pragmatically complex and often implicit, posing significant challenges for both human annotators and NLP systems. We develop a frame-based annotation scheme that captures the constitutive elements of moralizations - moral values, demands, and discourse protagonists - and apply it to a diverse set of German texts, including political debates, news articles, and online discussions. The corpus enables fine-grained analysis of moralizing language across communicative formats and domains. We further evaluate several large language models (LLMs) under varied prompting conditions for the task of moralization detection and moralization component extraction and compare it to human annotations in order to investigate the challenges of automatic and manual analysis of moralizations. Results show that detailed prompt instructions has a greater effect than few-shot or explanation-based prompting, and that moralization remains a highly subjective and context-sensitive task. We release all data, annotation guidelines, and code to foster future interdisciplinary research on moral discourse and moral reasoning in NLP.
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