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

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.