Triples extended to express three types of negation separately
Three Types of Negation of Triple and its Elements and an Extension of Triple
Artificial Intelligence
Summary
Traditional data models use triples to represent facts, but these triples mostly show things as true and struggle to express different types of ‘not true’. The authors explain that there are three kinds of negation: contradictory, opposite, and intermediary, that can apply to triples and their parts. They create an extended triple called the TCOI triple, which can handle these three negations independently, making it easier to represent complex negative information. Their method also allows for reasoning with these negatives, including applications in hypothetical questions called counterfactuals.
triple data modelnegation typescontradictory negationopposite negationintermediary negationsemantic data modelscounterfactual reasoningimplication reasoninglogical extensionstruth-value algorithms
Authors
Zhenghua Pan
Abstract
In various data models, the classical triple is a typical semantic data model. However, due to the design of the triple as a simple structure for representing positive assertions, it cannot sufficiently express different forms of negation present in the triple and its elements. This paper conceptually proposes that there are three distinct forms of negation within triples and their elements: contradictory negation, opposite negation and intermediary negation. Based on the the set SCOI and the logic LCOI+PLCOI with three kinds of negation, we propose an extension of triple that can distinguish and express these three different negations in the triple and its elements, called the TCOI triple with contradictory negation, opposite negation and intermediary negation. The TCOI triple is a semantic and structural extension of the classical triple. While retaining the ability to express positive assertions, it systematically introduces the three semantic dimensions of three negations, allowing these negations to independently act on the elements of the triple and on the whole triple. This significantly enhances the triple model capability to represent and reasoning about complex negative information. This paper also explores the expressive power and reasoning of the TCOI triple, as well as the application of TCOI triple implication reasoning in counterfactuals and counterfactual reasoning. We propose a truth-value (continuous value) algorithm for TCOI triple implication reasoning and perform its calculation through an example of the counterfactuals and counterfactual reasoning.