What NN architecture to predict fantasy character names based on description? I would like to build a neural network to predict a fantasy character name given a description.

Like 'Scar-faced long haired elf warrior' -> 'Glorfindel'

I have a dataset of about 12,000 fantasy names and description from various fantasy works. I  want to be able to map the description to names. Names are not vocabulary words and I want to NN to be able to generate new names for new description.

I wanted to use something like Elmo to embed the description and the name which would then easily teach the NN to map one to another, but the problem I faced is how do I go back from an embedding vector to characters representing a word.
First off, I think that since the goal of your model will be to generate new names based on a description, your model should work at a character-level and not word-level.

You can think of the level at which your model is working as the building blocks you are providing for it (it needs to learn them during training). These building blocks are than used for generation of new constructs. So if you want to construct new words (names) than you need to teach the model to understand the connection between the individual characters and the input description. Your model can deal with the input at a word-level but its output needs to be at character-level.

You can read more about it at: Besides Word Embedding, why you need to know Character Embedding?