Siberian State Medical University
E755165
Siberian State Medical University is a major Russian medical higher education and research institution located in Tomsk, known for training healthcare professionals for Siberia and beyond.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Siberian State Medical University canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8762400 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siberian State Medical University Context triple: [Tomsk, hasUniversity, Siberian State Medical University]
-
A.
Stavropol State Medical University
Stavropol State Medical University is a major Russian medical university known for training healthcare professionals and conducting medical research in the city of Stavropol.
-
B.
Kazan State Medical University
Kazan State Medical University is a major Russian medical higher education institution located in Kazan, known for training physicians and medical specialists and conducting biomedical research.
-
C.
Amur State Medical Academy
Amur State Medical Academy is a Russian medical university located in Blagoveshchensk that trains healthcare professionals and conducts medical research.
-
D.
Saratov State Medical University
Saratov State Medical University is a major Russian medical higher education and research institution located in the city of Saratov.
-
E.
Rostov State Medical University
Rostov State Medical University is a major Russian medical university located in Rostov-on-Don, known for training healthcare professionals and conducting medical research.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siberian State Medical University Target entity description: Siberian State Medical University is a major Russian medical higher education and research institution located in Tomsk, known for training healthcare professionals for Siberia and beyond.
-
A.
Stavropol State Medical University
Stavropol State Medical University is a major Russian medical university known for training healthcare professionals and conducting medical research in the city of Stavropol.
-
B.
Kazan State Medical University
Kazan State Medical University is a major Russian medical higher education institution located in Kazan, known for training physicians and medical specialists and conducting biomedical research.
-
C.
Amur State Medical Academy
Amur State Medical Academy is a Russian medical university located in Blagoveshchensk that trains healthcare professionals and conducts medical research.
-
D.
Saratov State Medical University
Saratov State Medical University is a major Russian medical higher education and research institution located in the city of Saratov.
-
E.
Rostov State Medical University
Rostov State Medical University is a major Russian medical university located in Rostov-on-Don, known for training healthcare professionals and conducting medical research.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
medical university
ⓘ
public university ⓘ |
| affiliation | Ministry of Health of the Russian Federation NERFINISHED ⓘ |
| continent |
Asia
ⓘ
Europe ⓘ |
| country | Russia ⓘ |
| engagesIn |
biomedical research
ⓘ
clinical research ⓘ medical research ⓘ |
| fieldOfStudy |
biomedical sciences
ⓘ
dentistry ⓘ medicine ⓘ nursing ⓘ pharmacy ⓘ public health ⓘ |
| hasAcademicDiscipline |
biochemistry
ⓘ
cardiology ⓘ clinical medicine ⓘ infectious diseases ⓘ internal medicine ⓘ microbiology ⓘ neurology ⓘ obstetrics and gynecology ⓘ oncology ⓘ pathology ⓘ pediatrics ⓘ pharmacology ⓘ public health and healthcare organization ⓘ surgery ⓘ |
| hasCampus | urban campus in Tomsk ⓘ |
| hasClinicalBase | teaching hospitals in Tomsk ⓘ |
| hasRole |
training dentists
ⓘ
training nurses ⓘ training pharmacists ⓘ training physicians ⓘ training public health specialists ⓘ |
| hasType |
higher education institution
ⓘ
research institution ⓘ |
| languageOfInstruction |
English
ⓘ
Russian ⓘ |
| locatedIn | Tomsk NERFINISHED ⓘ |
| locatedInAdministrativeTerritorialEntity | Tomsk Oblast NERFINISHED ⓘ |
| locatedInRegion | Siberia NERFINISHED ⓘ |
| offersProgram |
PhD programs
ⓘ
postgraduate medical education ⓘ residency training ⓘ undergraduate medical education ⓘ |
| partOf | Russian Federation higher education system ⓘ |
| regionServed | Siberian Federal District NERFINISHED ⓘ |
| servesRegion |
Russia
NERFINISHED
ⓘ
Siberia NERFINISHED ⓘ international students ⓘ |
| specializesIn | training healthcare professionals ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Siberian State Medical University Description of subject: Siberian State Medical University is a major Russian medical higher education and research institution located in Tomsk, known for training healthcare professionals for Siberia and beyond.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.