Even our central concept, event, is treated differently by the parties involved in our project; in the history domain, the notion of an event has been defined as “what agents make happen or undergo”[2]. This has the implication that actions are a species of events. Furthermore, events are concrete particulars. They are unrepeatable entities with a location in space and time[3]. Within computational linguistics, the notion of event is often not defined, and if defined, the definition is mostly pragmatic and broad to ensure reusability across different domains. Another difference is that in computer science ‘event extraction’ often does not stretch beyond the literal task of iden- tifying event labels, participants, locations and time stamps, whereas historians are interested in the interpretation of events. Computer science also considers events mostly as separate entities, whereas historians consider events in their connection with other events. The significance of an event depends on this connection and is usually expressed in the form of a narrative[4]. [...] Although there is no consensus on the definition of event in computer science, most event modelling approaches share the charac- teristic that they want to model: Who does what, where and when?. We take this as at least the minimal requirement an event modelling approach should be able to express. Once a minimal event definition has been developed, we can start to think about modelling additional aspects that play a role in our domain and are closely related to events, namely: granularity, interpretation, perspective, and causality. We are currently investigating the use of the simple event model (SEM) to model historical events[5]. SEM aims to provide the minimal set of classes to describe events, minimising possible clashes between different domain-specific event definitions.