The first experiment evaluates the individual contribution of different feature sets to SC classification accuracy.
a ME model is trained on the 55,629 training instances using the following feature sets separately: 1) unigram, 2) bigram, 3) first-last word, 4) head word (HW), 5) named entities (NE), 6) HW+WN CLASS, 7) HW+WN SIM, and 8) variants of HW+WN HYP.