论文标题
自动提取新闻（AESPEN）的社会政治事件：研讨会和共享任务报告
Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report
论文作者
论文摘要
我们描述了我们从新闻范围内的新闻和我们在语言资源和评估会议上组织的共同任务（LREC 2020）中组织的社会政治事件自动提取的努力。我们认为，计算语言学和社会和政治科学的活动提取研究应进一步相互支持，以便跨来源，国家和语言进行大规模的社会政治事件信息收集。该事件由常规的研究论文和共同的任务组成，这是关于事件句子核心身份识别（ESCI）的轨道。计划委员会的五名成员审查了所有提交。该研讨会吸引了与机器学习方法，语言资源，物质冲突预测的评估以及在社会政治事件信息收集范围内的共同任务参与报告有关的研究论文。它向我们展示了与社会政治事件有关的数据源和事件信息收集方法的数量和多样性，以及需要填补自动文本处理技术和社会和政治科学要求之间的空白。
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.
