Creating correct, semantic representations of questions is essential for applications that can use formal reasoning to answer them. However, even within a restricted domain, it is hard to anticipate all the possible ways that a question might be phrased, and engineer reliable processing modules to produce a correct semantic interpretation for the reasoner. In our work on posing questions to a biology knowledge base, we address this brittleness in two ways: First, we exploit the DIRT paraphrase database to introduce alternative phrasings of a question; Second, we defer word sense and semantic role commitment until question answering. Resulting ambiguities are then resolved by interleaving additional interpretation with question-answering, allowing the combinatorics of alternatives to be controlled and domain knowledge to guide paraphrase and sense selection. Our evaluation suggests that the resulting system is able to understand exam-style questions more reliably.