We focus on content word ED as one of the most challenging tasks in this area, illustrating our claims on adjective-noun (AN) combinations.
we (1) investigate the role of context in accurately capturing semantic anomalies and implement a system based on distributional topic coherence, which achieves state-of-the-art accuracy on a standard test set; (2) thoroughly investigate our system's performance across individual adjective classes, concluding that a classdependent approach is beneficial to the task; (3) discuss the data size bottleneck in this area, and highlight the challenges of automatic error generation for content words.