Generating language that reflects the temporal organization of represented knowledge requires a language generation model that integrates contemporary theories of tense and aspect, temporal representations, and methods to plan text. This paper presents a model that produces event combinations and appropriate connecting words to relate them. We distinguish between inherent and non-inherent aspectual features of verbs and describe an algorithm that uses these features to select tense, aspect, and temporal connecting words for generating text based on time-stamped information. The main result of this work is the successful incorporation of constrained linguistic theories of tense and aspect in a self-contained module called CONGEN that produces a ranked list of temporal connectives and tense/aspect possibilities from pairs of time-stamped literals. We show that the theoretical results described herein have been verified in a large-scale corpus analysis. The framework serves as the basis of a component designed to enhance the English output of a constrained generation system. (LAMP-TR-091) (UMIACS-TR-2002-71)