Simon Osindero
E81011
Simon Osindero is a machine learning researcher known for his influential work on deep learning and neural networks, including co-authoring foundational papers on deep belief nets.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Simon Osindero canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T645515 — 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: Simon Osindero Context triple: [A fast learning algorithm for deep belief nets, author, Simon Osindero]
-
A.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
-
B.
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.
-
C.
Ilya Sutskever
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
-
D.
Yoshua Bengio
Yoshua Bengio is a Canadian computer scientist and deep learning pioneer whose work on neural networks and representation learning has been foundational to modern artificial intelligence.
-
E.
Geoffrey Hinton
Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
- 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: Simon Osindero Target entity description: Simon Osindero is a machine learning researcher known for his influential work on deep learning and neural networks, including co-authoring foundational papers on deep belief nets.
-
A.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
-
B.
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.
-
C.
Ilya Sutskever
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
-
D.
Yoshua Bengio
Yoshua Bengio is a Canadian computer scientist and deep learning pioneer whose work on neural networks and representation learning has been foundational to modern artificial intelligence.
-
E.
Geoffrey Hinton
Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
- F. None of above. chosen
Statements (40)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
machine learning researcher ⓘ person ⓘ |
| coAuthorOf |
“A fast learning algorithm for deep belief nets”
ⓘ
surface form:
A fast learning algorithm for deep belief nets
|
| coAuthorWith |
Geoffrey Hinton
ⓘ
Iain Murray ⓘ Max Welling ⓘ Ruslan Salakhutdinov ⓘ Yee-Whye Teh ⓘ |
| educatedAt |
Imperial College London
ⓘ
University College London ⓘ University of Toronto ⓘ |
| employer |
DeepMind
ⓘ
surface form:
Google DeepMind
|
| fieldOfWork |
artificial intelligence
ⓘ
deep learning ⓘ machine learning ⓘ neural networks ⓘ |
| gender | male ⓘ |
| hasAcademicAdvisor | Geoffrey Hinton ⓘ |
| hasCitizenship | United Kingdom ⓘ |
| hasPublication |
“A fast learning algorithm for deep belief nets”
ⓘ
surface form:
A fast learning algorithm for deep belief nets
Modeling image patches with a directed hierarchy of Markov random fields ⓘ Topographic product models applied to natural scene statistics ⓘ |
| influencedBy | Geoffrey Hinton ⓘ |
| knownFor |
co-authoring foundational papers on deep belief nets
ⓘ
research on probabilistic models ⓘ research on unsupervised learning ⓘ |
| language | English ⓘ |
| memberOf | DeepMind ⓘ |
| nationality | British ⓘ |
| notableFor |
contributions to deep learning
ⓘ
work on deep belief networks ⓘ |
| position |
research leader in deep learning
ⓘ
research scientist at DeepMind ⓘ |
| researchInterest |
generative models
ⓘ
probabilistic graphical models ⓘ representation learning ⓘ unsupervised feature learning ⓘ |
| worksOn |
large-scale neural network models
ⓘ
scalable deep learning systems ⓘ |
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: Simon Osindero Description of subject: Simon Osindero is a machine learning researcher known for his influential work on deep learning and neural networks, including co-authoring foundational papers on deep belief nets.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
A fast learning algorithm for deep belief nets