An important part of question answering is ensuring a candidate answer is plausible as a response. We present a flexible approach based on discriminative preference ranking to determine which of a set of candidate answers are appropriate. Discriminative methods provide superior performance while at the same time allow the flexibility of adding new and diverse features. Experimental results on a set of focused What .? and Which .? questions show that our learned preference ranking methods perform better than alternative solutions to the task of answer typing. A gain of almost in MRR for both the first appropriate.
