This paper describes the largest scale annotation project involving the Enron email corpus to date. Over 12,500 emails were classified, by humans, into the categories “Business” and “Personal”, and then subcategorised by type within these categories. The paper quantifies how well humans perform on this task (evaluated by inter-annotator agreement). It presents the problems experienced with the separation of these language types. As a final section, the paper presents preliminary results using a machine to perform this classification task. .
