This paper presents a novel approach for meta-level information extraction (IE). The common IE process model is extended by utilizing transfer knowledge and meta-features that are created according to already extracted information. We present two real-world case studies demonstrating the applicability and benefit of the approach and directly show how the proposed method improves the accuracy of the applied information extraction technique.