Hyperintensional Reasoning based on Natural Language Knowledge Base
VSB-Technical University Ostrava（俄斯特拉发VSB技术大学）；Masaryk University（马萨里克大学）
Marie Duží, Aleš Horák
备注：
Preprint of an article accepted for publication in the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems \c{opyright} 2019 copyright World Scientific Publishing Company https://www.worldscientific.com/worldscinet/ijufks
The success of automated reasoning techniques over large natural-language texts heavily relies on a fine-grained analysis of natural language assumptions. While there is a common agreement that the analysis should be hyperintensional, most of the automatic reasoning systems are still based on an intensional logic, at the best. In this paper, we introduce the system of reasoning based on a fine-grained, hyperintensional analysis. To this end we apply Tichy's Transparent Intensional Logic (TIL) with its procedural semantics. TIL is a higher-order, hyperintensional logic of partial functions, in particular apt for a fine-grained natural-language analysis. Within TIL we recognise three kinds of context, namely extensional, intensional and hyperintensional, in which a particular natural-language term, or rather its meaning, can occur. Having defined the three kinds of context and implemented an algorithm of context recognition, we are in a position to develop and implement an extensional logic of hyperintensions with the inference machine that should neither over-infer nor under-infer.
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