Judea Pearl
E435765
Judea Pearl is a pioneering computer scientist and philosopher best known for his foundational work on probabilistic reasoning, Bayesian networks, and causal inference in artificial intelligence.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Judea Pearl canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T4379324 — 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: Judea Pearl Context triple: [Benjamin Franklin Medal in Computer and Cognitive Science, notableRecipient, Judea Pearl]
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A.
Andrew B. Moore
Andrew B. Moore was an American politician who served as governor of Alabama in the years leading up to and during the early part of the Civil War.
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B.
Dennis Michie
Dennis Michie was a U.S. Army officer and early football coach at West Point who is honored as the namesake of the United States Military Academy’s Michie Stadium.
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C.
Daphne Koller
Daphne Koller is a computer scientist and entrepreneur best known as the co-founder of the online education platform Coursera and for her influential work in probabilistic graphical models and machine learning.
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D.
Pedro Domingos
Pedro Domingos is a prominent computer scientist and machine learning researcher known for his influential work on data mining, probabilistic modeling, and the popular science book "The Master Algorithm."
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E.
Wolfram Burgard
Wolfram Burgard is a German computer scientist and roboticist known for his influential work in probabilistic robotics, autonomous navigation, and artificial intelligence.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Judea Pearl Target entity description: Judea Pearl is a pioneering computer scientist and philosopher best known for his foundational work on probabilistic reasoning, Bayesian networks, and causal inference in artificial intelligence.
-
A.
Andrew B. Moore
Andrew B. Moore was an American politician who served as governor of Alabama in the years leading up to and during the early part of the Civil War.
-
B.
Dennis Michie
Dennis Michie was a U.S. Army officer and early football coach at West Point who is honored as the namesake of the United States Military Academy’s Michie Stadium.
-
C.
Daphne Koller
Daphne Koller is a computer scientist and entrepreneur best known as the co-founder of the online education platform Coursera and for her influential work in probabilistic graphical models and machine learning.
-
D.
Pedro Domingos
Pedro Domingos is a prominent computer scientist and machine learning researcher known for his influential work on data mining, probabilistic modeling, and the popular science book "The Master Algorithm."
-
E.
Wolfram Burgard
Wolfram Burgard is a German computer scientist and roboticist known for his influential work in probabilistic robotics, autonomous navigation, and artificial intelligence.
- F. None of above. chosen
Statements (66)
| Predicate | Object |
|---|---|
| instanceOf |
academic
ⓘ
artificial intelligence researcher ⓘ author ⓘ computer scientist ⓘ philosopher ⓘ |
| academicDegree |
Bachelor's degree in electrical engineering
ⓘ
Master's degree in electrical engineering ⓘ PhD in electrical engineering ⓘ |
| academicDepartment |
Department of Computer Science, UCLA
NERFINISHED
ⓘ
Department of Statistics, UCLA NERFINISHED ⓘ |
| academicPosition | Professor ⓘ |
| almaMater |
Brooklyn Polytechnic Institute
NERFINISHED
ⓘ
Rutgers University NERFINISHED ⓘ Technion – Israel Institute of Technology NERFINISHED ⓘ |
| awardReceived |
AAAI Classic Paper Award
NERFINISHED
ⓘ
AAAS Fellow NERFINISHED ⓘ ACM A.M. Turing Award NERFINISHED ⓘ Benjamin Franklin Medal in Computer and Cognitive Science NERFINISHED ⓘ David E. Rumelhart Prize for Contributions to the Theoretical Foundations of Human Cognition NERFINISHED ⓘ Harold Pender Award NERFINISHED ⓘ Lakatos Award NERFINISHED ⓘ Rumelhart Prize NERFINISHED ⓘ Turing Award ⓘ |
| citizenship | United States of America ⓘ |
| coAuthor | Dana Mackenzie NERFINISHED ⓘ |
| countryOfBirth | Mandatory Palestine NERFINISHED ⓘ |
| dateOfBirth | 1936-09-04 ⓘ |
| employer | University of California, Los Angeles NERFINISHED ⓘ |
| familyName | Pearl NERFINISHED ⓘ |
| fieldOfWork |
Bayesian networks
NERFINISHED
ⓘ
artificial intelligence ⓘ causal inference ⓘ computer science ⓘ philosophy of science ⓘ probabilistic reasoning ⓘ |
| founded | Daniel Pearl Foundation NERFINISHED ⓘ |
| fullName | Judea Pearl NERFINISHED ⓘ |
| givenName | Judea NERFINISHED ⓘ |
| hasChild | Daniel Pearl NERFINISHED ⓘ |
| influenced |
machine learning research on causality
ⓘ
modern causal inference in statistics ⓘ philosophy of causation ⓘ |
| knownFor |
Bayesian networks
NERFINISHED
ⓘ
causal diagrams ⓘ do-calculus NERFINISHED ⓘ foundations of causal inference NERFINISHED ⓘ probabilistic reasoning in intelligent systems ⓘ structural causal models ⓘ |
| language |
English
ⓘ
Hebrew NERFINISHED ⓘ |
| memberOf |
American Academy of Arts and Sciences
ⓘ
Association for the Advancement of Artificial Intelligence NERFINISHED ⓘ National Academy of Engineering ⓘ National Academy of Sciences ⓘ |
| notableConcept |
causal hierarchy of association, intervention, and counterfactuals
ⓘ
ladder of causation NERFINISHED ⓘ |
| notableWork |
Causality: Models, Reasoning, and Inference
NERFINISHED
ⓘ
Probabilistic Reasoning in Intelligent Systems NERFINISHED ⓘ The Book of Why NERFINISHED ⓘ |
| placeOfBirth | Tel Aviv NERFINISHED ⓘ |
| researchContribution |
development of do-calculus for causal reasoning
ⓘ
formalization of causal inference using graphical models ⓘ integration of probability and logic in AI ⓘ semantics of counterfactuals in causal models ⓘ |
| spouse | Ruth Pearl NERFINISHED ⓘ |
| workInstitution | University of California, Los Angeles NERFINISHED ⓘ |
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: Judea Pearl Description of subject: Judea Pearl is a pioneering computer scientist and philosopher best known for his foundational work on probabilistic reasoning, Bayesian networks, and causal inference in artificial intelligence.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.