We need the inference so that we can know equivalence between classes and 
subclass relationships (eg "type 2 diabetes" is still "diabetes" because it's 
is a subclass of diabetes).

Another dataset that I've never been able to get to load with any inference 
enabled is SNOMED CT. Even when removing all of the owl inference that they 
have in their dataset and pre-calculating the direct subclass relationships, 
not even the transitive reasoner will load the dataset (without modification at 
runtime) once the first query is submitted after startup of Fuseki. Granted 
it's it significantly larger than ICD-10 CM. But still, not being able to load 
it with even pre-calculated direct subclass relationships is a huge deal 
breaker. Not to mention the fact that the real power of that dataset comes when 
the owl inference built into it can actually be used. With it, inference on 
patient data can reveal potential diagnoses that would not be inferred without 
and owl reasoning.

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