Event processing is an active area of research in the Natural Language Processing community, but resources and automatic systems developed so far have mainly addressed contemporary texts. However, the recognition and elaboration of events is a crucial step when dealing with historical texts Particularly in the current era of massive digitization of historical sources: Research in this domain can lead to the development of methodologies and tools that can assist historians in enhancing their work, while having an impact also on the field of Natural Language Processing. Our work aims at shedding light on the complex concept of events when dealing with historical texts. More specifically, we introduce new annotation guidelines for event mentions and types, categorized into 22 classes. Then, we annotate a historical corpus accordingly, and compare two approaches for automatic event detection and classification following this novel scheme. We believe that this work can foster research in a field of inquiry as yet underestimated in the area of Temporal Information Processing. To this end, we release new annotation guidelines, a corpus, and new models for automatic annotation.

中文翻译：

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历史文本的新事件检测和分类

事件处理是自然语言处理社区的一个活跃研究领域，但迄今为止开发的资源和自动系统主要针对当代文本。然而，在处理历史文本时，事件的识别和阐述是至关重要的一步，尤其是在当前历史资料大规模数字化的时代：该领域的研究可以导致方法论和工具的发展，这些方法和工具可以帮助历史学家加强他们的工作，同时也对自然语言处理领域产生影响。我们的工作旨在阐明在处理历史文本时事件的复杂概念。更具体地说，我们为事件提及和类型引入了新的注释指南，分为 22 个类别。然后，我们相应地注释一个历史语料库，并比较遵循这种新颖方案的两种自动事件检测和分类方法。我们相信，这项工作可以促进在时间信息处理领域尚未被低估的调查领域的研究。为此，我们发布了新的注释指南、语料库和自动注释的新模型。