1. A method for extracting a system modeling meta-model language model for a system from a natural language specification of the system, comprising: storing a natural language specification of a system in a computer memory; extracting, with a computer processor, syntactic structure from said natural language specification of a system, said syntactic structure representing a set of at least one syntactic subject; creating, with said computer processor, a first mapping between a predetermined said set of at least one syntactic subject and respective meta-model elements for a system modeling meta-model language, wherein said set of at least one syntactic subject comprises a noun phrase and said first mapping comprises a mapping of a respective noun phrase to said respective meta-model elements; extracting, with said computer processor, further syntactic structure representing a set of at least one syntactic predicate corresponding to each of said set of at least one syntactic subject; creating, with said computer processor, a second mapping between a predetermined set of at least one syntactic predicate and respective meta-model associations for said meta-model elements; creating, with said computer processor, at least one respective meta-model relation for each corresponding meta-model elements in accordance with any corresponding syntactic predicate identified in said extracted further syntactic structure; creating, with said computer processor, at least one of said respective meta-model elements in accordance with said first mapping for each identified said set of at least one syntactic subject; extracting, with said computer processor, at least one semantic element from said natural language specification; when a semantic element associated with a given predicate indicates that said given predicate is passive, a verb phrase from said given passive predicate is mapped, with said computer processor, as a meta-model reference between said meta-model elements for a corresponding subject and said meta-model elements for a corresponding object of said verb phrase, wherein a set of semantic elements comprises a set of optional semantic elements associated with said at least one of said subject or said object, which are mapped, with said computer processor, as at least one attribute of said corresponding meta-model elements; when said given predicate is active, a verb phrase from said given active predicate is mapped, with said computer processor, to a meta-model operation for said meta-model elements corresponding to said subject; said set of semantic elements comprises a set of optional semantic elements associated with said at least one of said subject or said object, which are mapped, with said computer processor, as at least one attribute of said corresponding meta-model elements, and thematic cluster data arranged to identify common semantic themes is determined from said set of optional semantic elements and transferred to said created at least one of said respective meta-model elements so as to enable the identification of said common semantic themes in said model of said system; and converting, with said computer processor, said created at least one of said respective meta-model elements into a model of said system.