Systems modelling with natural language and fuzzy logic

We appear to be surrounded by a multitude of concrete and abstract objects, which may be seen in terms of recurring, constant conjunction of properties. In linguistic terms such conjunctions are expressed as nouns, non-recurring conjunctions are symbolised as phrases or clauses. Such objects come into being, fade out of existence or, if already exist, can change their properties either as a result of a spontaneous process, chance or in accordance with a purpose i.e. as per specifications. An assembly of identified objects interacting in terms of physical power or influence, which carry the appropriate kind of energy or information, connected in a specific topology, and engaged in bringing about a change of property, is referred to as a system. The problem seems to be the lack of a comprehensive, inferential structure for evaluating the nature of outcomes of a situation. The author looks at how such an inferential structure can be created by converting aspects of natural language, the `raw symbolism´, into a formal language which is capable of being expressed as `chains´ of predicate logic terms carrying the adjectives, adverbs and verbs that can be written as fuzzy sets