Qualitative Spatial Reasoning for Question-Answering: Axiom Reuse and Algebraic Methods
by Uribe, T. E. and Chaudhri, V. and Hayes, P. J. and Stickel, M. E.
in AAAI Spring Symposium on Mining Answers from Texts and Knowledge Bases
Address: Stanford, CAKnowledge-based question answering relies on declarative knowledge and an inference procedure such as theorem proving. In this paper, we explore question answering based on spatial knowledge. We first consider a broad general-purpose axiomatic theory covering different aspects of qualitative spatial representation such as topology, orientation, distance, size, and shape. Since it can be expensive to build such a theory from scratch, we {\em heuristically slice\/} out a spatial subset of the Cyc knowledge base as a starting point for our work. We also explore a number of techniques to support efficient reasoning. The first is the RCC8 calculus, supported by the use of composition tables. We present a general-purpose mechanism for integrating composition tables into a first-order theorem prover. We also present a novel calculus to support reasoning with orientation. Finally, since a theoretical expressiveness analysis of such a broad spatial theory is not feasible, we develop a test suite of questions as a qualitative measure of the knowledge it captures. We also show how such a theory can serve as a special-purpose reasoning module in a larger system that is not limited to spatial queries.
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A Knowledge Entry System for Subject Matter ExpertsThe goal of SHAKEN project is to enable subject matter experts , without any assistance from AI technologists, to assemble the models of processes and mechanisms so that questions about them can be answered by declarative inference and simulation. |
| Name | Title | ||
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| Chaudhri, Vinay K | Program Director |  |
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Stickel, Mark E | Principal Scientist | |
| Uribe, Tomas E | Computer Scientist | |
