With the popularity of touch devices, pen + touch inputs have become mainstream input modes for mobile officing. However, existing applications mainly take one of them as input, which limits users’ interaction space. In addition, existing pen + touch research mainly focuses on serial pen + touch cooperation and parallel processing of specific interactive tasks and does not systematically consider parallel cooperation mechanism and intention correlation between different inputs. This study first proposes an interaction model based on pen + touch inputs and then defines pen + touch interaction primitives according to users’ behavioral habits in pen + touch cooperation, so as to extend pen + touch interaction space. Furthermore, by using a partially observable Markov decision process (POMDP), the study develops a method of extracting pen + touch input intentions based on time sequence information, so as to incrementally extract the interaction intention of polysemantic interaction primitives. Finally, the study evaluates the advantages of pen + touch inputs through a user experiment.