Linking refactor #233
Linking refactor #233
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scispacy/umls_utils.py
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| self.semantic_type_tree: UmlsSemanticTypeTree = construct_umls_tree_from_tsv( | ||
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| class MeshKnowledgeBase(KnowledgeBase): |
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I believe mesh terms have a tree as well, if one of us is able to find that tree somewhere on the internet it would be nice to package it here.
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They do, but the only reason we have the tree in there in the first place was because we were messing around with changing the granularity of the types for the NER model, which turned out to not be super useful. Also, the MESH KB lives in this hyper complex sparql database and I really don't want to figure out how to extract the tree haha
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lol fair enough. i do think that one of the pieces of value we add here is easy access to these kbs that are pretty complicated to figure out how to access (and people do use the type tree, or at least the levels of the types). so if its not too much work, it'd be great to extract and add, if its difficult, im fine letting it go.
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That's true - I'll add a TODO, maybe we can do it later. Mesh has a much better browser for viewing the entities, e.g https://meshb.nlm.nih.gov/record/ui?ui=D002430
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maybe just open an issue, and if someone has a compelling use case we can add it, or maybe they will add it :)
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Ok, I moved from |
This is an attempt to make it easier to load other KBs trained via the same mechanism as a pipeline.
Changes:
UmlsEntity->Entitytypesargument toUmlsEntityis now optional, as not every KB will have typesUmlsKnowledgeBaseintoKnowledgeBase, which doesn't hold the semantic type tree of UMLS.LinkerPathsnamedtuple, so we can reference groups of them by namenamearg to the linker and candidate generator, which is enough to construct the various pre-defined linkers we have.I'll actually add the MESH linker in a different PR to keep this one manageable.edit: Yolo it's not much extra code, i'll just add it here.
Once you've reviewed i'll add the data and stuff to s3!