Assume I have a list of sentences, which is just a list of strings. I need a way of comparing some input string against those sentences to find the most similar. Can ELMO embeddings be used to train a model that can give you the $n$ most similar sentences to an input string?
For reference, gensim provides a doc2vec model that can be trained on a list of strings, then you can use the trained model to infer a vector from some input string. That inferred vector can then be used to find the $n$ most similar vectors.
Could something similar be done, but using ELMO embedding instead?
Any guidance would be greatly appreciated.