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License: MIT License
A batteries-included kit for knowledge graphs
License: MIT License
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I suggest you use setuptools_scm
to automatically align __version__
in the Zincbase module with the version
property of the package to the git tags.
Sorry to open this as an issue, but I don't know of a better channel for ZincBase talk.
I am, wondering what is a good visualisation front end for ZincBase knowledge trees? From my understanding ZincBase used underneath networkx, so matplotlib is obviously a choice, but it is not very dynamic and easy to use for browser output.
Does anybody have experience with visualising Zincbase trees in some front ends?
Really cool project and loved your podcast!
I was tinkering around with the get_most_likely function as follows:
kb.from_csv('.//assets//countries_s3_train.csv',delimiter='\t')
kb.build_kg_model(cuda=False, embedding_size=40)
kb.train_kg_model(steps=2000, batch_size=1, verbose=True)
print(kb.get_most_likely('canada', 'locatedin', '?'))
And this results in:
[{'triple': ('canada', 'locatedin', 'central_asia'), 'prob': 0.8538}]
Unless I have my geography wrong :), do you think this is a result of the data being faulty? Or could I have done something wrong?
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