Julian Schrittwieser
E754250
Julian Schrittwieser is a computer scientist and AI researcher known for his work at DeepMind on advanced reinforcement learning and game-playing systems such as AlphaZero.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Julian Schrittwieser canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T8577102 — 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: Julian Schrittwieser Context triple: [Ioannis Antonoglou, coAuthorWith, Julian Schrittwieser]
-
A.
Demis Hassabis
Demis Hassabis is a British artificial intelligence researcher, neuroscientist, and entrepreneur best known as the co-founder and CEO of DeepMind, a leading AI company acquired by Google.
-
B.
Nicolas Heess
Nicolas Heess is a machine learning researcher known for his work in deep reinforcement learning, including contributions to algorithms such as Deep Deterministic Policy Gradient (DDPG).
-
C.
Shane Legg
Shane Legg is a computer scientist and AI researcher best known as a co-founder of DeepMind and for his influential work on artificial general intelligence.
-
D.
Oriol Vinyals
Oriol Vinyals is a prominent computer scientist and machine learning researcher known for his influential work on deep learning, sequence-to-sequence models, and reinforcement learning at leading AI labs.
-
E.
Sergey Levine
Sergey Levine is a prominent computer scientist and professor known for his influential research in deep reinforcement learning and robotics.
- 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: Julian Schrittwieser Target entity description: Julian Schrittwieser is a computer scientist and AI researcher known for his work at DeepMind on advanced reinforcement learning and game-playing systems such as AlphaZero.
-
A.
Demis Hassabis
Demis Hassabis is a British artificial intelligence researcher, neuroscientist, and entrepreneur best known as the co-founder and CEO of DeepMind, a leading AI company acquired by Google.
-
B.
Nicolas Heess
Nicolas Heess is a machine learning researcher known for his work in deep reinforcement learning, including contributions to algorithms such as Deep Deterministic Policy Gradient (DDPG).
-
C.
Shane Legg
Shane Legg is a computer scientist and AI researcher best known as a co-founder of DeepMind and for his influential work on artificial general intelligence.
-
D.
Oriol Vinyals
Oriol Vinyals is a prominent computer scientist and machine learning researcher known for his influential work on deep learning, sequence-to-sequence models, and reinforcement learning at leading AI labs.
-
E.
Sergey Levine
Sergey Levine is a prominent computer scientist and professor known for his influential research in deep reinforcement learning and robotics.
- F. None of above. chosen
Statements (25)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence researcher
ⓘ
computer scientist ⓘ software engineer ⓘ |
| areaOfExpertise |
deep reinforcement learning
ⓘ
game-playing neural networks ⓘ |
| contributedTo |
development of AlphaZero
ⓘ
research on general game-playing AI ⓘ |
| employer | DeepMind ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
game-playing algorithms ⓘ machine learning ⓘ reinforcement learning ⓘ |
| hasRole |
AI researcher
ⓘ
research engineer ⓘ |
| knownFor |
work on AlphaZero
ⓘ
work on game-playing AI systems ⓘ work on reinforcement learning ⓘ |
| notableWork |
AlphaZero
ⓘ
advanced reinforcement learning systems ⓘ |
| usesMethod |
Monte Carlo tree search
ⓘ
deep neural networks ⓘ self-play reinforcement learning ⓘ |
| workLocation |
London (DeepMind headquarters)
ⓘ
linked to:
London, England
|
| worksOn |
advanced game-playing systems
ⓘ
general-purpose reinforcement learning agents ⓘ |
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: Julian Schrittwieser Description of subject: Julian Schrittwieser is a computer scientist and AI researcher known for his work at DeepMind on advanced reinforcement learning and game-playing systems such as AlphaZero.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.