This paper describes a method for automatically extracting and classifying multiword expressions (MWEs) for Urdu on the basis of a relatively small unannotated corpus (around million tokens). The MWEs are extracted by an unsupervised method and classified into two distinct classes, namely locations and person names. The classification is based on simple heuristics that take the co-occurrence of MWEs with distinct postpositions into account.