I am interested in NLP, and i’m think about building a true/false answering system. I have training dataset including questions and labels (true / false), the answers are based on the wikipedia. For example, the question “Is Tom Cruise in the movie The Avengers?”, the answer is “false”. The basic idea is that treat a question as a query, and do information retrieval in wikipedia, and return true or false.
I’m thinking to use RNN model to build this system, but i am not very familiar with RNN, how should I put the training dataset and wikipedia data as inputs into the model?
I have this idea but I am not sure if it is correct, can I use the wikipedia data ONLY to train a RNN model, then use this trained model to train my training dataset for classification (as a transfer learning thing)?
Moreover, is there a way that besides answering true / false, but also returning evidences ? For example, the answer for a question is “true”, besides returning “true”, but also returning strings from wikipedia to support the answer.