Christof Koch
E262700
Christof Koch is a neuroscientist renowned for his pioneering work on the neural basis of consciousness and long collaboration with Francis Crick.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Christof Koch canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T2373530 — 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.
Target entity: Christof Koch Context triple: [Terrence Sejnowski, coAuthor, Christof Koch]
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A.
Terrence Sejnowski
Terrence Sejnowski is a pioneering computational neuroscientist and machine learning researcher known for foundational contributions to neural networks and learning algorithms.
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B.
Patricia Churchland
Patricia Churchland is a Canadian-American philosopher renowned for her pioneering work in neurophilosophy, exploring how neuroscience informs and reshapes traditional questions in philosophy of mind and ethics.
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C.
Olaf Sporns
Olaf Sporns is a neuroscientist known for his pioneering work in network neuroscience and the study of brain connectivity.
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D.
V. S. Ramachandran
V. S. Ramachandran is an Indian-American neuroscientist renowned for his pioneering work on visual perception, phantom limbs, and the neural basis of consciousness.
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E.
Norman E. Thagard
Norman E. Thagard is an American physician, former U.S. Marine Corps officer, and NASA astronaut who became the first American to fly on a Russian spacecraft.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Christof Koch Target entity description: Christof Koch is a neuroscientist renowned for his pioneering work on the neural basis of consciousness and long collaboration with Francis Crick.
-
A.
Terrence Sejnowski
Terrence Sejnowski is a pioneering computational neuroscientist and machine learning researcher known for foundational contributions to neural networks and learning algorithms.
-
B.
Patricia Churchland
Patricia Churchland is a Canadian-American philosopher renowned for her pioneering work in neurophilosophy, exploring how neuroscience informs and reshapes traditional questions in philosophy of mind and ethics.
-
C.
Olaf Sporns
Olaf Sporns is a neuroscientist known for his pioneering work in network neuroscience and the study of brain connectivity.
-
D.
V. S. Ramachandran
V. S. Ramachandran is an Indian-American neuroscientist renowned for his pioneering work on visual perception, phantom limbs, and the neural basis of consciousness.
-
E.
Norman E. Thagard
Norman E. Thagard is an American physician, former U.S. Marine Corps officer, and NASA astronaut who became the first American to fly on a Russian spacecraft.
- F. None of above. chosen
Statements (49)
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.
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.
Subject: Christof Koch Description of subject: Christof Koch is a neuroscientist renowned for his pioneering work on the neural basis of consciousness and long collaboration with Francis Crick.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.