Context-sensitive communication not only requires speakers to choose relevant utterances from alternatives, but also to retrieve and evaluate the relevant utterances from memory in the first place. In this work, we compared different proposals about how underlying semantic representations work together with higher-level selection processes to enable individuals to flexibly utilize context to guide their language use. We examined speaker and guesser performance in a two-player iterative language game based on Codenames, which asks speakers to choose a single `clue' word that allows their partner to select a pair of target words from a context of distractors. The descriptive analyses indicated that speakers were sensitive to the shared semantic neighborhood of the target word pair and were able to use guesser feedback to shift their clues closer to the unguessed word. We also formulated a series of computational models combining different semantic representations with different selection processes. Model comparisons suggested that a model which integrated contextualized lexical representations based on association networks with a contextualized model of pragmatic reasoning was better able to predict behavior in the game compared to models that lacked context at either the representational or process level. Our findings suggest that flexibility in communication is driven by context-sensitivity at at the level of both representations and processes.