Content segmentation in the context of laparoscopic videos is a challenging task due to the special characteristics of such video data. Common shot detection methods used in other domains do not work. Thus, we propose to use instrument classification, to enable a semantic segmentation of laparoscopic videos. The basic step for scene segmentation in an endoscopic video is the reliable detection of particular phases of an intervention. For laparoscopy this can be achieved via the recognition of surgery instruments. In particular, the appearance of one instrument, or a certain combination of instruments, signals the beginning of a new phase. In close cooperation with medical experts, we identified dependencies between six single workflow steps and instruments for cholecystectomy, i.e., the removal of the gallbladder. Thus, with the help of instrument classification for laparoscopic videos  we can segment laparoscopic videos into surgical phases .