I haven’t tried this yet, but the examples are very impressive. “We introduce a recursive neural network model that is able to correctly answer paragraph-length factoid questions from a trivia competition called quiz bowl. Our model is able to succeed where traditional approaches fail, particularly when questions contain very few words (e.g., named entities) indicative of the answer.”http://cs.umd.edu/~miyyer/qblearn/
IBM finally opening up the Watson system with an API. Allegedly the way to get access to this is via the BlueMix PAAS. https://developer.ibm.com/watson/docs/developing-watson-apis/ (I’ve tried this now. The Question Answering API is pretty much untrained and mostly gives bad results. However, its confidence scoring is very good, ie, if it gives a bad answer it will have a low confidence score, whereas answers with a 90%+ score are almost always right)
https://github.com/percyliang/sempre SEMPRE is a toolkit for training semantic parsers, which map natural language utterances to denotations (answers) via intermediate logical forms.