Hyperintensional Reasoning based on Natural Language Knowledge Base
| Autor: | Marie Duží, Aleš Horák |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer Science - Computation and Language
Transparent Intensional Logic Programming language Computer science business.industry Intensional logic 020207 software engineering Context (language use) 02 engineering and technology Term (logic) computer.software_genre Knowledge-based systems Knowledge base Artificial Intelligence Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Automated reasoning business computer Software Natural language Information Systems |
| Popis: | 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. Comment: 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 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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