论文标题
事件核心政治事件的核心解决方案
Event Coreference Resolution for Contentious Politics Events
论文作者
论文摘要
我们为事件核心分辨率提出了一个数据集，该数据集基于从多个来源，语言和国家 /地区绘制的随机样本。事件信息收集的早期奖学金尚未量化事件核心解决方案的贡献。我们准备并分析了代表性的多语言语料库，并测量了最先进的事件核心分辨率方法的绩效和贡献。我们发现，几乎一半的事件在文档中提到了与其他事件提及的同时发生的，这使得获得错误或部分事件信息是不可避免的。我们表明，事件核心解决方案可以帮助改善这种情况。我们的贡献阐明了迄今已被忽视或难以研究的挑战。可以根据我们在本报告中提出的结果设计未来的事件信息收集研究。这项研究的存储库在https://github.com/emerging-welfare/ecr4-contentious-politics上。
We propose a dataset for event coreference resolution, which is based on random samples drawn from multiple sources, languages, and countries. Early scholarship on event information collection has not quantified the contribution of event coreference resolution. We prepared and analyzed a representative multilingual corpus and measured the performance and contribution of the state-of-the-art event coreference resolution approaches. We found that almost half of the event mentions in documents co-occur with other event mentions and this makes it inevitable to obtain erroneous or partial event information. We showed that event coreference resolution could help improving this situation. Our contribution sheds light on a challenge that has been overlooked or hard to study to date. Future event information collection studies can be designed based on the results we present in this report. The repository for this study is on https://github.com/emerging-welfare/ECR4-Contentious-Politics.
