Amur State Medical Academy
E487919
Amur State Medical Academy is a Russian medical university located in Blagoveshchensk that trains healthcare professionals and conducts medical research.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Amur State Medical Academy canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5033662 — 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: Amur State Medical Academy Context triple: [Blagoveshchensk, hasHigherEducationInstitution, Amur State Medical Academy]
-
A.
Nizhny Novgorod State Medical Academy
Nizhny Novgorod State Medical Academy is a major Russian medical university known for training healthcare professionals and conducting medical research in the city of Nizhny Novgorod.
-
B.
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.
-
C.
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.
-
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.
Voronezh State Medical University
Voronezh State Medical University is a major Russian medical higher education institution known for training physicians and healthcare professionals and conducting biomedical 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: Amur State Medical Academy Target entity description: Amur State Medical Academy is a Russian medical university located in Blagoveshchensk that trains healthcare professionals and conducts medical research.
-
A.
Nizhny Novgorod State Medical Academy
Nizhny Novgorod State Medical Academy is a major Russian medical university known for training healthcare professionals and conducting medical research in the city of Nizhny Novgorod.
-
B.
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.
-
C.
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.
-
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.
Voronezh State Medical University
Voronezh State Medical University is a major Russian medical higher education institution known for training physicians and healthcare professionals and conducting biomedical research.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
higher education institution
ⓘ
medical university ⓘ |
| activity | conducting medical research ⓘ |
| collaboratesWith |
healthcare organizations in Amur Oblast
ⓘ
medical research institutes ⓘ regional hospitals ⓘ |
| country | Russia ⓘ |
| educationalFocus |
medical education
ⓘ
training healthcare professionals ⓘ |
| fieldOfStudy |
healthcare
ⓘ
medical sciences ⓘ medicine ⓘ |
| governedBy |
Ministry of Health of the Russian Federation
ⓘ
Ministry of Science and Higher Education of the Russian Federation ⓘ |
| hasAcademicDiscipline |
clinical medicine
ⓘ
internal medicine ⓘ medical biology ⓘ medical diagnostics ⓘ obstetrics and gynecology ⓘ pediatrics ⓘ pharmacology ⓘ public health ⓘ surgery ⓘ |
| hasCampus | urban campus in Blagoveshchensk ⓘ |
| hasRole | training medical personnel for regional healthcare system ⓘ |
| languageOfInstruction | Russian ⓘ |
| locatedIn |
Amur Oblast
ⓘ
Blagoveshchensk ⓘ Russian Far East ⓘ
linked to:
Russia Far East
|
| offersProgram |
clinical internship programs
ⓘ
postgraduate medical programs ⓘ residency training ⓘ undergraduate medical programs ⓘ |
| organizationType | non-profit educational institution ⓘ |
| regionServed |
Amur Oblast
ⓘ
Russian Far East ⓘ
linked to:
Russia Far East
|
| researchFocus |
biomedical research
ⓘ
clinical research ⓘ public health research ⓘ |
| sector | public education sector ⓘ |
| specializesIn |
training nurses
ⓘ
training other healthcare workers ⓘ training physicians ⓘ |
| typeOfInstitution | state medical academy ⓘ |
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: Amur State Medical Academy Description of subject: Amur State Medical Academy is a Russian medical university located in Blagoveshchensk that trains healthcare professionals and conducts medical research.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.