Moving QA Towards Reading Comprehension Using Context and Default Reasoning

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For a question answering system to understand the underlying assumptions and contextual features of natural language, a contextually and semantically sensitive knowledge representation and reasoning module is essential. This paper proposes a three-layered knowledge representation coupled with reasoning mechanisms for defaults and contexts as a solution for pushing question answering towards a state capable of basic reading comprehension. A travel scenario is presented as a vehicle for demonstrating the complexities of this problem, and the ways in which semantic relations, contexts (for conditionality, planning, time, and space), and defaults address these complexities.