SemRep #16
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Priority: Low
This issue can be dealt with in long term or is on hold
Status: Suggested
This issue is a suggestion for doing something new or different in CovidGraph
SemRep is a UMLS-based program that extracts three-part propositions, called semantic predications, from sentences in biomedical text. Predications consist of a subject argument, an object argument, and the relation that binds them. For example, from the sentence in (1), SemRep extracts the predications in (2).
We used hemofiltration to treat a patient with digoxin overdose that was complicated by refractory hyperkalemia.
Hemofiltration-TREATS-Patients
Digoxin overdose-PROCESS_OF-Patients
hyperkalemia-COMPLICATES-Digoxin overdose
Hemofiltration-TREATS(INFER)-Digoxin overdose
The subject and object arguments of each predication are concepts from the UMLS Metathesaurus and their binding relationship (in uppercase) is a relation from the UMLS Semantic Network. For a detailed description of SemRep, see [1].
Holders of a UMLS license can run SemRep interactively or in batch mode using the SKR Scheduler. SemRep is also available as a stand-alone program on the Linux platform.
https://semrep.nlm.nih.gov/
Suggested by Ben Elsworth - Not sure if this will be helpful, but i've annotated the literature text into subject-predicate-object triples using SemRep (https://semrep.nlm.nih.gov/)?
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