Abstract
This paper presents an approach to the problem of factual Question Generation. Factual questions are questions whose answers are specific facts: who?, what?, where?, when?. We enhanced a simple attribute-value (XML) language and its interpretation engine with context-sensitive primitives and added a linguistic layer deep enough for the overall system to score well on user satisfiability and the ’linguistically well-founded’ criteria used to measure up language generation systems. Experiments with open-domain question generation on TREC-like data validate our claims and approach.
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Rus, V., Cai, Z., Graesser, A.C. (2007). Experiments on Generating Questions About Facts. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2007. Lecture Notes in Computer Science, vol 4394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70939-8_39
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DOI: https://doi.org/10.1007/978-3-540-70939-8_39
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