MEMMs are a type of graphical model used for sequence labeling that combines features of HMMs and MaxEnt models. They are discriminative models that extend standard maximum entropy classifiers by assuming the unknown values to be learnt are connected in a Markov chain. MEMMs are used in natural language processing, specifically in part-of-speech tagging and information extraction.