NECE: Narrative Event Chain Extraction Toolkit

Authors
Xu, Guangxuan
Toro Isaza, Paulina
Li, Moshi
Oloko, Akintoye
Yao, Bingsheng
Sanctos, Cassia
Adebiyi, Aminat
Hou, Yufang
Peng, Nanyun
Wang, Dakuo
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Issue Date
2022-07-17
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Attribution-NonCommercial-NoDerivs 3.0 United States
Full Citation
Guangxuan Xu, Paulina Toro Isaza, Moshi Li, Akintoye Oloko, Bingsheng Yao, Cassia Sanctos, Aminat Adebiyi, Yufang Hou, Nanyun Peng, & Dakuo Wang. (2023). NECE: Narrative Event Chain Extraction Toolkit.
Abstract
To understand a narrative, it is essential to comprehend its main characters and the associated major events; 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 using sliding window method. Through extensive human evaluations, we have confirmed the high quality of the NECE toolkit, and external validation has demonstrated its potential for application in downstream tasks such as question answering and bias analysis. The NECE toolkit includes both a Python library and a user-friendly web interface; the latter offers custom visualizations of event chains and easy navigation between graphics and text to improve reading efficiency and experience.
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arXiv
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