To solve crimes, investigators often rely on interviews with witnesses, victims, or criminals themselves. The interviews are transcribed and the pertinent data is contained in narrative form. To solve one crime, investigators may need to interview multiple people and then analyze the narrative reports. There are several difficulties with this process: interviewing people is time consuming, the interviews - sometimes conducted by multiple officers - need to be combined, and the resulting information may still be incomplete. For example, victims or witnesses are often too scared or embarrassed to report or prefer to remain anonymous. We are developing an online reporting system that combines natural language processing with insights from the cognitive interview approach to obtain more information from witnesses and victims. We report here on information extraction from police and witness narratives. We achieved high precision, 94% and 96%, and recall, 85% and 90%, for both narrative types.