1. A method for identifying names, personalities, titles, and topics, whether or not said names, personalities, titles and topics are present in a given repository, comprising extracting candidate search terms from unstructured published content by any of named entity extraction (NEE); topic detection and tracking (TDT); direct human intervention; natural language processing; and a combination of NEE, TDT, direct human intervention, and natural language processing; storing said candidate search terms in a historical database of candidate search terms; storing a history of said extracted search term candidates; extracting verified search terms from internal sources of said repository; matching candidate search terms against verified search terms by applying linguistic edit distance techniques to obtain plausible linguistic variants of verified search terms; using said linguistic variants to generate augmented verified search terms; storing a history of said augmented verified search terms; establishing a set of null search terms comprising candidate search terms having a threshold incidence count in said history of said extracted search term candidates and in said history of said augmented verified search terms; and adding a set of search terms comprising any of said augmented verified search terms and said null search terms to any of an automatic speech recognition or natural language processing system.