用大模型生成中文通用情感事件，构建首个大规模情感事件知识库。
Acquiring Common Chinese Emotional Events Using Large Language Model
- 用情感指标提示中文大模型生成事件，再通过过滤器去噪。
- 获得102,218条带情感极性的高质量中文情感事件。
- 适合做情感原因抽取、心理分析等场景的中文认知计算研究。
情感事件知识是提升多种应用效果的重要基础，但通用、情境无关的情感事件难以获取。本文旨在构建中文通用情感事件知识库，如“获奖”、“被批评”。方法首先收集全面的中文情感事件指示词，随后利用中文大语言模型（LLM）以这些指示词为提示生成情感事件。为保证质量，训练一个过滤器剔除无效生成结果，并采用不同技术对事件进行正负情感分类。最终获得102,218条高质量、带情感极性标签的通用中文情感事件，是目前唯一大规模中文情感事件常识知识库。内在评估表明该方法有效；外在应用案例也展示了其在情感原因抽取（ECE）中的强潜力。相关资源将在论文发表后公开。
原文摘要 · Abstract (English)
Knowledge about emotional events is an important kind of knowledge which has been applied to improve the effectiveness of different applications. However, emotional events cannot be easily acquired, especially common or generalized emotional events that are context-independent. The goal of this paper is to obtain common emotional events in Chinese language such as "win a prize" and "be criticized". Our approach begins by collecting a comprehensive list of Chinese emotional event indicators. Then, we generate emotional events by prompting a Chinese large language model (LLM) using these indicators. To ensure the quality of these emotional events, we train a filter to discard invalid generated results. We also classify these emotional events as being positive events and negative events using different techniques. Finally, we harvest a total of 102,218 high-quality common emotional events with sentiment polarity labels, which is the only large-scale commonsense knowledge base of emotional events in Chinese language. Intrinsic evaluation results show that the proposed method in this paper can be effectively used to acquire common Chinese emotional events. An extrinsic use case also demonstrates the strong potential of common emotional events in the field of emotion cause extraction (ECE). Related resources including emotional event indicators and emotional events will be released after the publication of this paper.
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