论文标题
通过Barthes的基本功能在叙述中建模事件显着性
Modeling Event Salience in Narratives via Barthes' Cardinal Functions
论文作者
论文摘要
叙事中的事件在显着性上有所不同：有些对故事更重要。估计事件显着性对于诸如故事的生成和叙事学和民俗学的文本分析等任务很有用。为了在没有任何注释的情况下计算事件显着性，我们采用了Barthes对事件显着性的定义，并提出了几种仅需要预训练的语言模型的无监督方法。通过事件显着性注释，评估有关民间故事的提议方法，我们表明，所提出的方法优于基线方法，并在叙事文本上找到对语言模型的微调是改进提出的方法的关键因素。
Events in a narrative differ in salience: some are more important to the story than others. Estimating event salience is useful for tasks such as story generation, and as a tool for text analysis in narratology and folkloristics. To compute event salience without any annotations, we adopt Barthes' definition of event salience and propose several unsupervised methods that require only a pre-trained language model. Evaluating the proposed methods on folktales with event salience annotation, we show that the proposed methods outperform baseline methods and find fine-tuning a language model on narrative texts is a key factor in improving the proposed methods.
