If I understand correctly, you are trying to predict the correct choice in a multiple choice question.
there are many things to consider before creating a model.
first of all, do you have a dataset of multiple choice questions and the correct answer?
second of all, is your dataset in a certain domain or over multiple domains? what I mean by this, is that, are your questions all in physics, or they are also in math, chemistry, etc.
because these kind of tasks are very domain-specific.
one way to design this, is to put some detectable word like {BLANK} in your corpus.
next for every sentence in your dataset, you will fill every blank by this word.
then you design an RNN model, that takes the sentence sequence as input and the correct word in corpus as output. (this would be a one hot coding vector)
model your sentences as a sequence of words, then give it to your RNN network as input.
I think the network, given that is trained for enough epochs, learns to associate the {BLANK} with the correct word.