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As part of the event course of, we put together a crew of computational linguists and subject material consultants to develop a core Natural Language Processing (NLP) engine using statistical and rules-based paperrater NLP to extract language features from essays and robustly translate that into statistical models. The tip product is a state-of-the-art system combining Automated Grammatical Error Detection, Automated Essay Scoring, Automated Proofreading, and plagiarism detection.