When dealing with a phenomenon as vast and com plex as natural language, an experimental approach is often the best way to discover new computational methods and determine their usefulness. The experimental process includes designing and selecting new experiments, carrying out the experiments, and evaluating the experiments. Most conference presentations are about finished experiments, completed theoretical results, or the evaluation of systems already in use. In this workshop setting, I would like to depart from this tendency to discuss some experiments that we are beginning to perform, and the reasons for investigating a particular approach to parsing. This approach builds on recent work in unification-based parsing and classification-based knowledge representation, developing an architecture that brings together the capabilities of these related frameworks.