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View Code? Open in Web Editor NEWGraph Convolutional Networks (GCN) with BERT for Coreference Resolution Task [Pytorch][DGL]
Graph Convolutional Networks (GCN) with BERT for Coreference Resolution Task [Pytorch][DGL]
Hi all,
I was wondering if it is possible to use custom data that one can prepare themselves for training this model. If so, how does one do this with RGCN-with-BERT? Will it convert a txt file to the right format or does one have to convert it to a ConLL file first? Can it be ConLL-U? Thank you very much.
does r-gcn works on entity alignment (existing R-GCN seems only focus on classification and link prediction)?
If yes, May I know do you have any working code on this?
It's interesting to apply BERT on the coreference resolution, I wonder if there is a related paper for further reading?
Thanks!
token_lst = pickle.load(open('token_lst_wto_padding.pkl', "rb"))
offsets_lst = pickle.load(open('offsets_lst.pkl', "rb"))
This two statements call for two pkl files which not offer in this repo. Can you give a sample case of these two pkl files? It would be better if you can upload :)
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