Journalists often localize news stories that are not explicitly about the community they serve by investigating and describing how those stories affect that community. This is, in essence, a form of personalization based not on a reader's personal interests, but rather on their ties to a geographic location. In this paper we present The Local Angle, an approach for automating the process of finding national and international news stories that are locally relevant. The Local Angle associates the people, companies, and organizations mentioned in news stories with geographic locations using semantic analysis tools and online knowledge bases. We describe the design and implementation of our prototype system that helps content curators and consumers discover articles that are of local interest even if they do not originate locally.