1. A computer implemented question answering method, comprising: (a) receiving or accessing a natural language question; (b) recognizing one or more entity surfaces in the natural language question, and generating one or more corresponding template surface queries; (c) constructing one or more structured queries based on one or more trained models for queried templates and entities; (d) finding and selecting one or more answer phrases using constructed structured queries on a knowledge base; and (e) composing, or initiating the composition, of output based on the one or more answer phrases.
1. A computer implemented question answering method, comprising: (a) receiving or accessing a natural language question; (b) recognizing one or more entity surfaces in the natural language question, and generating one or more corresponding template surface queries; (c) constructing one or more structured queries based on one or more trained models for queried templates and entities; (d) finding and selecting one or more answer phrases using constructed structured queries on a knowledge base; and (e) composing, or initiating the composition, of output based on the one or more answer phrases. 4. The method of claim 1 , wherein the step of selecting one or more answer phrases using constructed structured queries comprises: (a) employing a ranking scheme considering following factors: (i) popularity of the templates surface; (ii) popularity of entities; (iii) probability of relation path corresponding to the template; and (iv) the depth of the nesting structured queries.