1. A method to facilitate authoring of a Bayesian Belief Network (BBN) comprising: accessing natural language text content of documents stored in a content storage device said natural language text content includes text units; identifying statements within said accessed natural language text content indicating a probabilistic dependence relation; extracting said statements indicating said probabilistic dependence relation from said natural language text content; parsing said extracted statement to generate a directed typed-dependency graph structure, said graph structure having nodes associated with words of said text unit, and said nodes being interconnected and associated with a label denoting a grammatical relation among said nodes; a parsed text unit including non-restrictive relative clauses and restrictive relative clauses; breaking a directed typed-dependency graph into one or more subgraphs, a subgraph corresponding to restrictive relative clauses and a subgraph corresponding to non-restrictive relative clauses; each said subgraph processed separately to obtain evidence statements; and aggregating said extracted statements and evidence statements to form a BBN network structure, wherein a programmed processing unit performs said identifying, statement extracting, and aggregating.
1. A method to facilitate authoring of a Bayesian Belief Network (BBN) comprising: accessing natural language text content of documents stored in a content storage device said natural language text content includes text units; identifying statements within said accessed natural language text content indicating a probabilistic dependence relation; extracting said statements indicating said probabilistic dependence relation from said natural language text content; parsing said extracted statement to generate a directed typed-dependency graph structure, said graph structure having nodes associated with words of said text unit, and said nodes being interconnected and associated with a label denoting a grammatical relation among said nodes; a parsed text unit including non-restrictive relative clauses and restrictive relative clauses; breaking a directed typed-dependency graph into one or more subgraphs, a subgraph corresponding to restrictive relative clauses and a subgraph corresponding to non-restrictive relative clauses; each said subgraph processed separately to obtain evidence statements; and aggregating said extracted statements and evidence statements to form a BBN network structure, wherein a programmed processing unit performs said identifying, statement extracting, and aggregating. 6. The method as claimed in claim 1 , wherein said aggregating said extracted statements comprises: determining statements having a same pair of variables; reconciling statements having a same pair of variables; and creating a directed acyclic graph associated with the reconciled statements.