Question Classification is the task of classifying a question based on the expected answer. As an example, the question “Who is the prime minister?” could be assigned the class “person”, whereas the question “Where is the prime minister?” could belong to the class “location”. Since the task involves identifying the type of answer, it is sometimes referred to as Answer Type Classification. The Question Classification system developed by us, was at COLING2016, is state of the art and achieves an accuracy of 97.2%.
You can make use of the Question Classification API: Take a look at the documentation.
C16-1116 [bib]: Harish Tayyar Madabushi; Mark Lee
High Accuracy Rule-based Question Classification using Question Syntax and Semantics Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers (Coling 2016). 2016
Also take a look at our work on Semantic Text Similarity, which was presented at SemEval 2016.