We describe our effort on automated extraction of socio-political events from
news in the scope of a workshop and a shared task we organized at Language
Resources and Evaluation Conference (LREC 2020). We believe the event
extraction studies in computational linguistics and social and political
sciences should further support each other in order to enable large scale
socio-political event information collection across sources, countries, and
languages. The event consists of regular research papers and a shared task,
which is about event sentence coreference identification (ESCI), tracks. All
submissions were reviewed by five members of the program committee. The
workshop attracted research papers related to evaluation of machine learning
methodologies, language resources, material conflict forecasting, and a shared
task participation report in the scope of socio-political event information
collection. It has shown us the volume and variety of both the data sources and
event information collection approaches related to socio-political events and
the need to fill the gap between automated text processing techniques and
requirements of social and political sciences.

本研究旨在自动从新闻中提取社会政治事件，并讨论计算语言学和社会政治学研究在大规模跨源、跨国和跨语言的社会政治事件信息收集中的相互支持，研究内容包括机器学习方法学的评估、语言资源、物质冲突预测、核心参照识别等。