<p>SpanBERT is a version of BERT pre-trained to produce useful embeddings on text spans. SpanBERT itself has nothing to do with coreference resolution. The original paper is <a href="https://arxiv.org/abs/1907.10529" rel="nofollow noreferrer">https://arxiv.org/abs/1907.10529</a>, and the original source code is <a href="https://github.com/facebookresearch/SpanBERT" rel="nofollow noreferrer">https://github.com/facebookresearch/SpanBERT</a>, though you might have an easier time using the huggingface version at <a href="https://huggingface.co/SpanBERT" rel="nofollow noreferrer">https://huggingface.co/SpanBERT</a>.</p>
<p>It is definitely possible to get the embeddings as output, along with the coreference predictions. I recommend cloning <a href="https://github.com/allenai/allennlp-models" rel="nofollow noreferrer">https://github.com/allenai/allennlp-models</a>, getting it to run in your environment, and then changing the code until it gives you the output you want.</p>
Information about Embeddings in the Allen Coreference Model
<p>I'm an Italian student approaching the NLP world.
First of all I'd like to thank you for the amazing work you've done with the paper &quot; Higher-order Coreference Resolution with Coarse-to-fine Inference&quot;.
I am using the model provided by allennlp library and I have two questions for you.</p>
<ol>
<li><p>in <a href="https://demo.allennlp.org/coreference-resolution" rel="nofollow noreferrer">https://demo.allennlp.org/coreference-resolution</a> it is written that the embedding used is SpanBERT. Is this a BERT embedding trained regardless of the coreference task? I mean, could I possibly use this embedding just as a pretrained model on the english language to embed sentences? (e.g. like <a href="https://huggingface.co/facebook/bart-base" rel="nofollow noreferrer">https://huggingface.co/facebook/bart-base</a> )</p>
</li>
<li><p>is it possible to modify the code in order to return, along with the coreference prediction, also the aforementioned embeddings of each sentence?</p>
</li>
</ol>
<p>I really hope you can help me.
Meanwhile I thank you in advance for your great availability.
Sincerely,
Emanuele Gusso</p>