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"Mesh" and "Hpo" linkers give the same result #463
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Hi, there are two components related to entity recognition and linking in scispacy. One is the Named Entity Recognition (NER) component, which identifies textual spans that are likely to be entities (and depending on which scipsacy model, also their broad type). This information can be accessed as you've done via |
I have a similar question. In the above example itself, in spite of using |
All of the ontology options are implemented as subsets of UMLS. We don't have any cross mapping to the root ontology identifier. You would have to get that from UMLS or another source. The entity information available from UMLS in scispacy can be accessed as in the example code linker = nlp.get_pipe("scispacy_linker")
for umls_ent in entity._.kb_ents:
print(linker.kb.cui_to_entity[umls_ent[0]]) |
Then how do linkers like |
They link to subsets of UMLS that are more specific than the full UMLS. This can be useful for two reasons (at least two that come to mind) if you know that you just want entities that fall into one of those subsets, 1) the downloaded file is much smaller and memory usage is less 2) the results will be higher precision because you won't get links to entities of a different type that you are not interested in. |
The mesh and hpo linker entities should contain the exact same information as the umls linker entities since they are just a subset. |
Hi,
I'm trying to annotate data using Scispacy. Loading "mesh" and "hpo" gives the exact same results no matter what is the input.
For example:
I tried on many texts and both linkers plotted the same results.
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