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This paper revisits the problem of complex word identification (CWI)following up the SemEval CWI shared task. We use ensemble classifiers toinvestigate how well computational methods can discriminate between complex andnon-complex words. Furthermore, we analyze the classification performance tounderstand what makes lexical complexity challenging. Our findings show thatmost systems performed poorly on the SemEval CWI dataset, and one of thereasons for that is the way in which human annotation was performed.

Complex Word Identification: Challenges in Data Annotation and System Performance