To understand a narrative, it is essential to comprehend the temporal event flows, especially those associated with main characters; however, this can be challenging with lengthy and unstructured narrative texts. To address this, we introduce NECE, an open-access, document-level toolkit that automatically extracts and aligns narrative events in the temporal order of their occurrence. Through extensive evaluations, we show the high quality of the NECE toolkit and demonstrates its downstream application in analyzing narrative bias regarding gender. We also openly discuss the shortcomings of the current approach, and potential of leveraging generative models in future works. Lastly the NECE toolkit includes both a Python library and a user-friendly web interface, which offer equal access to professionals and layman audience alike, to visualize event chain, obtain narrative flows, or study narrative bias.

翻译：摘要：理解叙事需要把握时间性的事件流，尤其是与主要角色相关的事件序列，然而冗长且非结构化的叙事文本对此构成了挑战。为解决这一问题，我们提出了NECE，一个开放获取的文档级工具包，能够自动提取叙事事件并按其发生的时间顺序进行对齐。通过广泛评估，我们验证了NECE工具包的高质量，并展示了其在分析性别相关叙事偏见方面的下游应用。我们还公开讨论了当前方法的局限性，以及未来工作中利用生成模型的潜力。最后，NECE工具包包含Python库和用户友好的Web界面，为专业人士和普通用户提供同等访问权限，以可视化事件链、获取叙事流或研究叙事偏见。