This paper presents a simple framework for extracting information found in publications or documents that are issued in large volumes and which cover similar concepts or issues within a given domain. The general aim of the work described, is to present a model for automatically augmenting segments of these documents with metadata using dynamically acquired background domain knowledge in order to assist users in easily locating information within these documents through a structured front end. To realize this goal, both document structure as well as dynamically acquired background knowledge, are utilized. A real life example where these ideas have been applied is also presented.