Stanislav Nikolov
E736804
Stanislav Nikolov is a researcher known for co-authoring the landmark 2021 Nature paper on AlphaFold, the deep learning system for highly accurate protein structure prediction.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Stanislav Nikolov canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8482650 — 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: Stanislav Nikolov Context triple: [Jumper et al., Nature 2021, hasAuthor, Stanislav Nikolov]
-
A.
Vladimir Tenev
Vladimir Tenev is a Bulgarian-American entrepreneur best known as the co-founder and CEO of the commission-free trading platform Robinhood Markets.
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B.
Georgi Todorov
Georgi Todorov was a Bulgarian general who played a prominent command role in the Balkan Wars and World War I.
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C.
Krastyo Georgiev Stanchev
Krastyo Georgiev Stanchev, better known as Christian Rakovsky, was a prominent Bulgarian-Romanian socialist revolutionary, diplomat, and Soviet political figure active in the early 20th century.
-
D.
Boris Slavov
Boris Slavov is a video game music composer best known for his cinematic scores on major titles such as the Crysis series and Divinity: Original Sin 2.
-
E.
Vulko Chervenkov
Vulko Chervenkov was a Bulgarian communist politician who served as the country’s de facto leader in the early 1950s, overseeing a period of strict Stalinist rule and rapid industrialization.
- 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: Stanislav Nikolov Target entity description: Stanislav Nikolov is a researcher known for co-authoring the landmark 2021 Nature paper on AlphaFold, the deep learning system for highly accurate protein structure prediction.
-
A.
Vladimir Tenev
Vladimir Tenev is a Bulgarian-American entrepreneur best known as the co-founder and CEO of the commission-free trading platform Robinhood Markets.
-
B.
Georgi Todorov
Georgi Todorov was a Bulgarian general who played a prominent command role in the Balkan Wars and World War I.
-
C.
Krastyo Georgiev Stanchev
Krastyo Georgiev Stanchev, better known as Christian Rakovsky, was a prominent Bulgarian-Romanian socialist revolutionary, diplomat, and Soviet political figure active in the early 20th century.
-
D.
Boris Slavov
Boris Slavov is a video game music composer best known for his cinematic scores on major titles such as the Crysis series and Divinity: Original Sin 2.
-
E.
Vulko Chervenkov
Vulko Chervenkov was a Bulgarian communist politician who served as the country’s de facto leader in the early 1950s, overseeing a period of strict Stalinist rule and rapid industrialization.
- F. None of above. chosen
Statements (23)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
deep learning system ⓘ researcher ⓘ scientific article ⓘ |
| coAuthorOf | 2021 Nature paper on highly accurate protein structure prediction with AlphaFold ⓘ |
| contributedTo | development of AlphaFold ⓘ |
| developer | DeepMind NERFINISHED ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
computational biology ⓘ machine learning ⓘ protein structure prediction ⓘ protein structure prediction ⓘ |
| hasAuthor | Stanislav Nikolov NERFINISHED ⓘ |
| hasPublicationYearForNotableWork | 2021 ⓘ |
| knownFor |
deep learning research
ⓘ
work on AlphaFold ⓘ |
| mainSubject |
AlphaFold
NERFINISHED
ⓘ
protein structure prediction ⓘ |
| notableWork | 2021 Nature AlphaFold paper ⓘ |
| publicationVenueOfNotableWork | Nature NERFINISHED ⓘ |
| publicationYear | 2021 ⓘ |
| publishedIn | Nature NERFINISHED ⓘ |
| worksOn | deep learning systems for protein structure prediction ⓘ |
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: Stanislav Nikolov Description of subject: Stanislav Nikolov is a researcher known for co-authoring the landmark 2021 Nature paper on AlphaFold, the deep learning system for highly accurate protein structure prediction.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.