Abstract
This paper describes a knowledge-based methodology of mining textual answers from large collections of texts. We present an answer engine capable of providing answers to any question posed in natural language, regardless of the domain of interest. The answers are produced by combining semantic data from question taxonomies with information abductively inferred from texts. The high precision of the retrieved answers is due to novel, efficient knowledge processing techniques.
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