BERT and SpanBERT for Coreference Resolution
# 🌟 New model addition

## Model description

This is a recent approach for co-reference resolution using BERT, implemented from the papers [BERT for Coreference Resolution: Baselines and Analysis](https://arxiv.org/abs/1908.09091) and [SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://arxiv.org/abs/1907.10529), which is the current state of the art on OntoNotes (79.6 F1). It uses tensorflow 1.14.0.

Reason why this is interesting is it achieves strong improvements on the OntoNotes (+3.9 F1) and GAP (+11.5 F1) benchmarks. Also, I think it would be a nice addition to huggingface library, as it has only the neuralcoref as the coreference resolution module.

## Open source status

* [x] the model implementation is available: (https://github.com/mandarjoshi90/coref)
* [x] the model weights are available: (https://github.com/facebookresearch/SpanBERT)
* [x] who are the authors: (@mandarjoshi90, @jkkummerfeld, @wenyudu)

Commenting for visibility - is this available now ? can't seem to find it, would love to use this for a question-answering project i'm working on! <|||||>I'd also like to see this model incorporated into the core list of supported models. I did note that you can download it from the community models here though: https://huggingface.co/SpanBERT/spanbert-base-cased<|||||>Are there any translations of the above repository (https://github.com/mandarjoshi90/coref) into the awesome HuggingFace API ? That would be very cool to test :D !<|||||>I would like to work on this...but will need some guidance