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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.
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 !
🌟 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 and SpanBERT: Improving Pre-training by Representing and Predicting Spans, 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
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