PREMO is a knowledge-based Preference Semantics parser with access to a large, lexical semantic knowledge base and organized along the lines of an operating system. The state of every partial parse is captured in a structure called a language object, and the control structure of the preference machine is a priority queue of these language objects. The language object at the front of the queue has the highest score as computed by a preference metric that weighs grammatical predictions, semantic type matching, and pragmatic coherence. The highest priority language object is the intermediate reading that is currently most preferred (the others are still “alive,” but not actively pursued); in this way the preference machine avoids combinatorial explosion by following a “best-first” strategy for parsing. The system has clear extensions into parallel processing.