1. A method, comprising: receiving, at a computing device from a searcher, a search query having location ambiguity; generating, by the computing device, a location model using a machine learning technique, the location model generated, at least in part, based on a personalization feature, wherein the personalization feature comprises a location corresponding to a past result selected by the searcher, wherein generating the location model based, at least in part, on the personalization feature comprises generating a training dataset comprising the personalization feature, wherein generating the training dataset comprises filtering a query log to identify a first query, the first query specifying an unambiguous location, generating, from the first query, a second query having location ambiguity by removing a first component of the first query, wherein removing the first component comprises breaking the first query into the first component and a second component, and removing the first component, identifying a location candidate for the second query, and generating a training target based on comparing the unambiguous location specified in the first query and the location candidate for the second query; identifying, by the computing device using the location model, an unambiguous location for the search query to resolve the location ambiguity; and determining, by the computing device, a search result corresponding to the search query directed to the unambiguous location for the search query.