To understand how strong n-grams are when evaluated in our leave-one-prompt-out crossvalidation setting, we employ them as features in our second baseline.
we train a multiclass classifier on our data set using a feature set composed solely of unigram, bigram, and trigram features, each of which indicates the number of times the corresponding n-gram is present in the associated essay.