Abstract
In this paper, first we propose constraints on natural language propositions involving fuzzy quantifiers by truth-qualification. For example, for the proposition"Most tall men are heavy is true", we consider that constrains exist between height and weights of men, so between grade values of the fuzzy set"TALL"and those of the fuzzy set"HEAVY"of the men. Second under the constraints, we propose an inference method for natural language propositions involving fuzzy quantifiers, for example"Most tall men are heavy is true". For the proposition, we can infer a modified proposition "Many tall men are very heavy is true", where the fuzzy quantifier"Many"in the inferred proposition can be resolved analytically, according to the modifier"very". Generally, for natural language propositions involving three types of quantifiers, a monotone nonincreasing type(few, …), a monotone nondecreasing type(most, …)and a convex type(several, …)and monotone truth-qualifiers(true, false, …), we can resolve fuzzy quantifiers analytically for propositions transformed in fuzzy predicates.
