A Generalized Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers and Truth Qualifiers
Ryosuke Fujioka, Atsushi Inoue, Shun’ichi Tano, Wataru Okamoto · 2005
In this paper, we propose a generalized inference method needed for constructing a natural language communication system. The method is used to obtain fuzzy quantifier Q' when "Q are F is taurArr Q'(m'A) are mF is m" is tau" is inferred (Q, Q': fuzzy quantifiers, A: fuzzy subject, m, m', m": modifiers, F: fuzzy predicate, tau : truth qualifier). We show that Q' is resolved step by step for two types of Q, including a non-increasing type (few,...) and a non-decreasing type (most,...)