While an increasing amount of studies exploring named entity recognition in historical corpora are published, application of other information extraction tasks such as event extraction remains scarce. This study explores two accessible methods to facilitate the detection of events and the classification of entities into roles: rule-based systems and RNN-based machine learning techniques. We focus on a German-language corpus from the 15th-17th c. and property purchases as the event types. We show that these relatively simple methods can retrieve useful information and discuss ideas to further enhance the results.