This paper presents an approach to creating flexible general-logic representations from language for use in high-level reasoning tasks in cognitive modeling. These representations are grounded in a large-scale ontology and emphasize the need for semantic breadth at the cost of syntactic breadth. The task-independent interpretation process allows task-specific pragmatics to guide the interpretation process. In the context of a particular cognitive model, we discuss our use of limited abduction for interpretation and show results of its performance.
Emmett Tomai, Kenneth D. Forbus