Check If Answer for a Question is Correct by Similarity Let's say in an NLP problem, I have a question and some correct answers to that question (say, 10 correct answers). 

Is there a way to get a new answer as input, and "calculate" whether it is correct?
This problem can be solved better if you also include the background text from where the questions have been picked up. Then, firstly train word embeddings on the background text. Further, generate sentence compositionality of the questions as well as their answers using a Recursive Neural Network or some variant. After all these steps you can compute the similarity between compositions of the new answer and given answers to know if it is correct or not.