A TABOO-NOT in OPEN World Assumption for A Natural Language based Logic Programming
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Abstract
Traditional logic programs are written in some formal languages easy to “unify” each other or symbol based ones such as in Prolog, and their “NOT” mechanisms are “negation by failure of proof” according to “CLOSED world assumption” and are not assumed as “true negation”s.On the other hand, we suppose that BigData for moral, ethics and values are written originally in various different natural languages over the world.In order for both human and AI to easily understand and automatically operate such BigData, we hope that (1) human could logic-program the contents of such Big-Data, by semi-dead-copying the original-natural-language-texts as "logic-programs" without hard translation, formalization and/or normalization,(2) “NOT”s in the language text that mean some TABOOs in any culture shall be operated correctly as such (not as “negataion by failure of proof”s but as the TABOOs) even in case of concretizing objects from different cultures, as in OPEN world assumption, because any TABOO from any one culture shall be rigidly respected, even during meetings between people from different cultures including the one culture with the TABOO.For the above purpose, this document explains a method of natural-language-based-logic-programming where variables for knowledge abstraction and concretization are embedded into the natural language texts, and also explains the above strong "TABOO-NOT" implementation therefor.
Publication details
- DOI
- 10.1109/bigdata55660.2022.10020810
- OpenAlex
- W4320024203
- Document type
- conference-paper
- Language
- EN
- Source
- 2022 IEEE International Conference on Big Data (Big Data)
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