  Relation and event extraction is an important task in natural language
processing. We introduce a system which uses contextualized knowledge graph
completion to classify relations and events between known entities in a noisy
text environment. We report results which show that our system is able to
effectively extract relations and events from a dataset of wet lab protocols.
