Rule-Based Link Prediction over Event-Related Causal Knowledge in Wikidata
Rich semantic information contained in Wikidata about newsworthy events and their causal relations may serve as a valuable resource to perform event analysis and forecasting. However, prior work in leveraging methods such as link prediction over causal event data in knowledge graphs has been limited. In this work we share our methods and findings to curate a dataset of newsworthy events with cause-effect relations and apply rule-based link prediction models. We find that the performance of such models can vary greatly among the various relations contained in our curated data, and we identify several points of consideration for both the data curation process and model performance when using knowledge about events that are currently present in Wikidata.