11. The method as claimed in claim 1 , wherein building, a skeleton of a natural language lexicon leverages open data to populate the skeleton initially wherein the ontology classes of the source model are matched to classes of open data.
1. A method for generating a natural language model for a specific information domain, comprising: building a skeleton of a natural language lexicon for the specific information domain from a source model of the specific information domain, the skeleton comprising terms found in the source model, the source model comprising classification hierarchies for the terms, the terms including objects and attributes; using the skeleton of the natural language lexicon to form a dictionary; applying a set of syntactical rules defining concepts and relationships to the dictionary; expanding the skeleton of the natural language lexicon based on a plurality of reference documents from the specific information domain, wherein expanding the skeleton comprises: clustering and scoring terms for concepts and relationships, and an intersection component for intersecting the syntactic rules and the clustered concepts and relationships; and using the expanded skeleton of the natural language lexicon, provide a natural language processing model for the specific information domain, the natural language processing model utilized by a user in the specific information domain to analyze documents in the specific information domain.