SeRI:A Dataset for Sub-event Relation Inference from an Encyclopedia

摘要：

　　Mining sub-event relations of major events is an important research problem,which is useful for building event taxonomy,event knowledge base construction,and natural language understanding.To advance the study of this problem,this paper presents a novel dataset called SeRI(Sub-event Relation Inference).SeRI includes 3,917 event articles from English Wikipedia and the annotations of their sub-events.It can be used for training or evaluating a model that mines sub-event relation from encyclopedia-style texts.Based on this dataset,we formally define the task of sub-event relation inference from an encyclopedia,propose an experimental setting and evaluation metrics and evaluate some baseline approaches performance on this dataset.

作者: Tao Ge Lei Cui Baobao Chang Zhifang Sui Furu Wei Ming Zhou

作者单位: School of EECS,Peking University,Beijing,China;Microsoft Research Asia,Beijing,China Microsoft Research Asia,Beijing,China School of EECS,Peking University,Beijing,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 268-277

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）