In this short paper, we present our preliminary results on building a Knowledge Graph (KG) of events and consequences with application to event forecasting and analysis. A base KG is first constructed using existing concepts and relations in Wikidata. Using an automated unsupervised knowledge extraction pipeline, causal knowledge is extracted from Wikipedia articles to augment the base KG. We show examples from the base and the augmented KG, and discuss a few challenges in building a high-quality KG. We also discuss a few potential directions that the Wikidata community can work on to improve the representation of event-related knowledge in Wikidata.