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首页> 外文会议>Workshop on Automated Event Extraction of Socio-political Events from News >Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report
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Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report

机译：从新闻中自动提取社会政治事件（AESPEN）：研讨会和共享任务报告

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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.
机译：我们将在研讨会的范围内描述我们从新闻中自动提取社会政治事件的努力，以及在语言资源和评估会议（LREC 2020）上组织的一项共同任务。我们认为，计算语言学和社会政治学中的事件提取研究应进一步相互支持，以便能够跨来源，国家和语言进行大规模的社会政治事件信息收集。该事件由常规研究论文和一项共同任务组成，该任务涉及事件句子共指代识别（ESCI）跟踪。计划委员会的五名成员审核了所有提交的内容。研讨会吸引了与机器学习方法评估，语言资源，重大冲突预测有关的研究论文，以及在社会政治事件信息收集范围内的共享任务参与报告。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种类，以及填补自动文本处理技术与社会政治学要求之间的空白的需求。

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