Oleg Krasnov
E863035
Oleg Krasnov is a person notable enough to be recognized as a significant bearer of the Krasnov surname.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Oleg Krasnov canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5815885 — 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: Oleg Krasnov Context triple: [Krasnov, hasNotableBearer, Oleg Krasnov]
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A.
Oleg Baklanov
Oleg Baklanov was a Soviet politician and high-ranking official who played a key role as one of the hardline plotters in the failed 1991 coup attempt against Mikhail Gorbachev.
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B.
Oleg Klimov
Oleg Klimov is a researcher known for his contributions to the development and analysis of Proximal Policy Optimization (PPO) algorithms in reinforcement learning.
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C.
Andrei Voronkov
Andrei Voronkov is a computer scientist known for his influential work in automated reasoning and theorem proving.
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D.
Mikhail Zharov
Mikhail Zharov was a prominent Soviet film and theater actor known for his character roles in classic Russian cinema.
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E.
Sergey Sokolov
Sergey Sokolov was a Soviet military leader and Marshal of the Soviet Union who served as the USSR’s Minister of Defense during the 1980s.
- 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: Oleg Krasnov Target entity description: Oleg Krasnov is a person notable enough to be recognized as a significant bearer of the Krasnov surname.
-
A.
Oleg Baklanov
Oleg Baklanov was a Soviet politician and high-ranking official who played a key role as one of the hardline plotters in the failed 1991 coup attempt against Mikhail Gorbachev.
-
B.
Oleg Klimov
Oleg Klimov is a researcher known for his contributions to the development and analysis of Proximal Policy Optimization (PPO) algorithms in reinforcement learning.
-
C.
Andrei Voronkov
Andrei Voronkov is a computer scientist known for his influential work in automated reasoning and theorem proving.
-
D.
Mikhail Zharov
Mikhail Zharov was a prominent Soviet film and theater actor known for his character roles in classic Russian cinema.
-
E.
Sergey Sokolov
Sergey Sokolov was a Soviet military leader and Marshal of the Soviet Union who served as the USSR’s Minister of Defense during the 1980s.
- F. None of above. chosen
Statements (6)
| Predicate | Object |
|---|---|
| instanceOf | human ⓘ |
| hasFamilyName | Krasnov NERFINISHED ⓘ |
| hasGender | male ⓘ |
| hasGivenName | Oleg NERFINISHED ⓘ |
| hasNotability | notable bearer of the Krasnov surname ⓘ |
| hasSurname | Krasnov NERFINISHED ⓘ |
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: Oleg Krasnov Description of subject: Oleg Krasnov is a person notable enough to be recognized as a significant bearer of the Krasnov surname.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.