text: Title: Implement CopyNext model
  Body: https://api.semanticscholar.org/CorpusID:225103260
  
  This is similar to [`CopyNet`](https://docs.allennlp.org/models/main/models/generation/models/copynet_seq2seq/#copynetseq2seq) from [Gu et al., 2016](https://api.semanticscholar.org/CorpusID:8174613), but adds an inductive bias for copying contiguous tokens.
  
  ~~The implementation is actually just a simple extension of `CopyNet`: `CopyNext` introduces a special symbol in the target vocabulary - the "CopyNext Symbol" (CN) - which corresponds to the operation of copying another token. So the CN token always follows a copied token that is the first in its span or another CN token.~~ -- As @JohnGiorgi pointed out below, CopyNext uses a separate linear layer to calculate the "CN" score. And there are some other differences with this model as well. Most notably, they make a big simplification by treating all tokens in the source sequence as unique, and not worrying about the case where a source token may be part of the target vocabulary. This makes sense for the task that CopyNext was applied to (nested NER), but not general seq2seq tasks.