This dissertation draws on three retrieval tasks to identify important properties of retrieval systems supporting the use of structure and annotations. We investigate known-item finding of web pages, retrieving elements from XML articles, and the retrieval of answer-bearing sentences as a component of a question-answering system. The retrieval model, an adaptation of the Inference Network model, clarifies the query language and simplifies the process of smoothing using multiple representations. The experiments in this dissertation show state-of-the-art results for these tasks and also provide novel insights to the shape of the parameter space when using mixtures of language models. Our experiments with question-answering further show how semantic predicates automatically annotated on a collection can be used to improve a system's ability to retrieve answer-bearing sentences.
