My goal is to predict the most appropriate answer from an utterance, in a group of 21 potential answers.

Example:

Utterance: How are you today? Answers: Answer1, 2, ..., 21.

I have a training file with this format:

Utterance: Answers: Good answer, wrong answer1, wrong answer2,..., wrong answer20.

My problem

For the first time, we have to make a prediction from a group of possible answers, and, thus, this is a MCQ form.

Any ideas how I could start the problem?

What I've done

For the moment, the only thing I did was to choose the answers from the 21 possible answers which had the highest cosine similarity with the utterance. (So, unsupervised). It's not that bad (24% against 1/21 at random), but I'm sure there are ways to make something really better.

What I don't want to do at first

Use a generative model which predicts a full sentence. I want to choose the best candidate amongs the 21 answers, and use the training file which can allow us to do supervised learning.