This paper presents a concept recognition system for European and national legislation. Current named entity recognition (NER) systems do not focus on identifying concepts which are essential for interpretation and harmonization of European and national law. We utilized the IATE (Inter-Active Terminology for Europe) vocabulary, a state-of-the-art named entity recognition system and Wikipedia to generate an annotated corpus for concept recognition. We applied conditional random fields (CRF) to identify concepts on a corpus of European directives and Statutory Instruments (SIs) of the United Kingdom. The CRF-based concept recognition system achieved an F1 score of 0.71 over the combined corpus of directives and SIs. Our results indicate the usability of a CRF-based learning system over dictionary tagging and state-of-the-art methods.
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