论文标题

NECE:叙事事件链提取工具包

NECE: Narrative Event Chain Extraction Toolkit

论文作者

Xu, Guangxuan, Isaza, Paulina Toro, Li, Moshi, Oloko, Akintoye, Yao, Bingsheng, Sanctos, Cassia, Adebiyi, Aminat, Hou, Yufang, Peng, Nanyun, Wang, Dakuo

论文摘要

要了解叙事,必须理解时间事件流动,尤其是与主要角色相关的事件。但是,通过冗长而非结构化的叙事文本,这可能具有挑战性。为了解决这个问题,我们介绍了一个开放式,文档级工具包NECE,该工具包自动以其发生的时间顺序提取和对齐叙事事件。通过广泛的评估,我们展示了NECE工具包的高质量,并在分析有关性别的叙事偏见中展示了其下游应用。我们还公开讨论当前方法的缺点,以及在未来工作中利用生成模型的潜力。最后,NECE工具包既包括Python库和用户友好的Web界面,这些界面提供了与专业人士和外行受众的平等访问,以可视化事件链,获得叙事流或学习叙事偏见。

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.

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