极小模型和部分蕴涵语义在人工智能很多领域中有着广泛的应用.本文分析当前件和后件分别是文字、文字集和公式时,极小模型和部分蕴涵语义的复杂性问题并做相关讨论.结果表明,随着前件和后件越复杂,相关的判定问题复杂度越高.而这些判定问题的复杂度都在多项式谱系的前两层之内. Minimal model and some implication semantics are widely used in many fields of artificial intelligence.This paper analyzes the complexity of the semantic model and some implication semantics when the current and the postulate are text, The results show that the more complex the antecedent and the consequent, the more complex the relevant decision problems, and the complexity of these decision problems is within the first two layers of the polynomial pedigree.