Thore Graepel
E802575
Thore Graepel is a German computer scientist and machine learning researcher known for his work at DeepMind on game-playing AI systems and reinforcement learning.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Thore Graepel canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9500705 — 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: Thore Graepel Context triple: [AlphaGo Zero, hasAuthor, Thore Graepel]
-
A.
Max Welling
Max Welling is a prominent machine learning researcher known for foundational contributions to probabilistic deep learning and Bayesian inference, including co-developing variational autoencoders.
-
B.
Martin Riedmiller
Martin Riedmiller is a German computer scientist and pioneer in deep reinforcement learning, known for his influential work on neural-network-based control and contributions to landmark deep RL systems.
-
C.
Christopher J. C. Burges
Christopher J. C. Burges is a computer scientist and machine learning researcher known for his contributions to pattern recognition and support vector machines.
-
D.
Samy Bengio
Samy Bengio is a prominent machine learning researcher known for his contributions to deep learning and his leadership roles at major AI organizations including Google and Apple.
-
E.
Jonathon Shlens
Jonathon Shlens is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work at Google.
- 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: Thore Graepel Target entity description: Thore Graepel is a German computer scientist and machine learning researcher known for his work at DeepMind on game-playing AI systems and reinforcement learning.
-
A.
Max Welling
Max Welling is a prominent machine learning researcher known for foundational contributions to probabilistic deep learning and Bayesian inference, including co-developing variational autoencoders.
-
B.
Martin Riedmiller
Martin Riedmiller is a German computer scientist and pioneer in deep reinforcement learning, known for his influential work on neural-network-based control and contributions to landmark deep RL systems.
-
C.
Christopher J. C. Burges
Christopher J. C. Burges is a computer scientist and machine learning researcher known for his contributions to pattern recognition and support vector machines.
-
D.
Samy Bengio
Samy Bengio is a prominent machine learning researcher known for his contributions to deep learning and his leadership roles at major AI organizations including Google and Apple.
-
E.
Jonathon Shlens
Jonathon Shlens is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work at Google.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
machine learning researcher ⓘ |
| academicDegree | PhD in computer science ⓘ |
| affiliation |
DeepMind
NERFINISHED
ⓘ
Microsoft Research NERFINISHED ⓘ University College London NERFINISHED ⓘ |
| countryOfCitizenship | Germany ⓘ |
| educatedAt |
Christian-Albrechts-Universität zu Kiel
NERFINISHED
ⓘ
Royal Holloway, University of London NERFINISHED ⓘ |
| employer |
DeepMind
NERFINISHED
ⓘ
Google DeepMind NERFINISHED ⓘ Microsoft Research NERFINISHED ⓘ University College London NERFINISHED ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
computer science ⓘ game theory ⓘ machine learning ⓘ reinforcement learning ⓘ |
| hasAcademicAdvisor | Rudolf Kruse NERFINISHED ⓘ |
| hasGender | male ⓘ |
| knownFor |
contributions to AlphaGo
ⓘ
contributions to AlphaZero ⓘ work on game-playing AI systems ⓘ work on reinforcement learning ⓘ |
| languageOfWorkOrName |
English
ⓘ
German ⓘ |
| memberOf | academic staff of University College London ⓘ |
| notablePublication |
papers on game-theoretic machine learning
ⓘ
papers on reinforcement learning for games ⓘ |
| notableWork |
AlphaGo
NERFINISHED
ⓘ
AlphaZero NERFINISHED ⓘ game-playing AI systems ⓘ reinforcement learning for games ⓘ |
| occupation |
computer scientist
ⓘ
researcher ⓘ university professor ⓘ |
| positionHeld |
principal researcher at Microsoft Research
ⓘ
professor of machine learning at University College London ⓘ research scientist at DeepMind ⓘ |
| researchInterest |
Bayesian methods
ⓘ
game-theoretic machine learning ⓘ multi-agent systems ⓘ online learning ⓘ probabilistic modeling ⓘ |
| workLocation |
London, England
ⓘ
surface form:
London
United Kingdom ⓘ |
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: Thore Graepel Description of subject: Thore Graepel is a German computer scientist and machine learning researcher known for his work at DeepMind on game-playing AI systems and reinforcement learning.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.