Annotation is important for personal photo collections because acquired metadata plays a crucial role in image management and retrieval. Bulk annotation, where multiple images are annotated at once, is a desired feature for image management tools because it reduces users' burden when making annotations. This paper describes an approach for automatically creating meaningful image clusters for efficient bulk annotation. These techniques are not perfect and so are integrated into a bulk annotation interface where users can manually correct errors. We present hierarchical event clustering and torso based human identification techniques. Hierarchical event clustering provides multiple levels of “event” groups. For identifying people in images, we introduce a new technique which uses torso information rather than human facial features.