John Alan Robinson
E46382
John Alan Robinson was a pioneering logician and computer scientist best known for introducing the resolution principle, a fundamental method in automated theorem proving and logic programming.
All labels observed (1)
| Label | Occurrences |
|---|---|
| John Alan Robinson canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T364389 — 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: John Alan Robinson Context triple: [Herbrand Award, notableRecipient, John Alan Robinson]
-
A.
Wilhelm Ackermann
Wilhelm Ackermann was a German mathematician known for his work in mathematical logic and the development of the Ackermann function, one of the earliest-discovered examples of a computable but not primitive recursive function.
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B.
Zellig Harris
Zellig Harris was an influential American linguist known for his pioneering work in structural linguistics and discourse analysis, and for mentoring Noam Chomsky.
-
C.
Marvin Minsky
Marvin Minsky was an American cognitive scientist and pioneering artificial intelligence researcher who co-founded MIT's AI Laboratory and made foundational contributions to the theory and philosophy of AI.
-
D.
Albert W. Tucker
Albert W. Tucker was a Canadian-born American mathematician best known for his influential work in game theory and topology, including formulating the Prisoner’s Dilemma and mentoring John Nash.
-
E.
Alonzo Church
Alonzo Church was an American mathematician and logician best known for developing lambda calculus and making foundational contributions to computability theory and mathematical logic.
- 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: John Alan Robinson Target entity description: John Alan Robinson was a pioneering logician and computer scientist best known for introducing the resolution principle, a fundamental method in automated theorem proving and logic programming.
-
A.
Wilhelm Ackermann
Wilhelm Ackermann was a German mathematician known for his work in mathematical logic and the development of the Ackermann function, one of the earliest-discovered examples of a computable but not primitive recursive function.
-
B.
Zellig Harris
Zellig Harris was an influential American linguist known for his pioneering work in structural linguistics and discourse analysis, and for mentoring Noam Chomsky.
-
C.
Marvin Minsky
Marvin Minsky was an American cognitive scientist and pioneering artificial intelligence researcher who co-founded MIT's AI Laboratory and made foundational contributions to the theory and philosophy of AI.
-
D.
Albert W. Tucker
Albert W. Tucker was a Canadian-born American mathematician best known for his influential work in game theory and topology, including formulating the Prisoner’s Dilemma and mentoring John Nash.
-
E.
Alonzo Church
Alonzo Church was an American mathematician and logician best known for developing lambda calculus and making foundational contributions to computability theory and mathematical logic.
- F. None of above. chosen
Statements (40)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
logician ⓘ person ⓘ |
| academicDiscipline |
computer science
ⓘ
logic ⓘ philosophy ⓘ |
| awardReceived |
CAI Distinguished Research Award
ⓘ
Herbrand Award ⓘ |
| birthDate | 1930 ⓘ |
| birthPlace |
Yorkshire, England
ⓘ
linked to:
Yorkshire
|
| contributedTo |
foundations of logic programming
ⓘ
resolution-based theorem provers ⓘ |
| countryOfCitizenship |
United Kingdom
ⓘ
United States of America ⓘ |
| deathDate | 2016 ⓘ |
| educatedAt |
Cambridge University
ⓘ
Princeton University ⓘ |
| employer | Syracuse University ⓘ |
| familyName | Robinson ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
automated theorem proving ⓘ logic programming ⓘ mathematical logic ⓘ |
| fullName | John Alan Robinson ⓘ |
| givenName | John ⓘ |
| hasResearchInterest |
automated deduction
ⓘ
first-order logic ⓘ non-classical logics ⓘ |
| influenced |
development of Prolog
ⓘ
research in automated reasoning ⓘ research in logic programming ⓘ |
| inspired |
SLD-resolution in logic programming
ⓘ
development of resolution-based proof procedures in AI ⓘ |
| introduced | resolution principle ⓘ |
| knownFor | 1965 paper on a machine-oriented logic based on the resolution principle ⓘ |
| languageOfWorkOrName | English ⓘ |
| notableFor |
automated deduction
ⓘ
contributions to logic programming ⓘ resolution principle ⓘ |
| positionHeld | professor of computer science at Syracuse University ⓘ |
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: John Alan Robinson Description of subject: John Alan Robinson was a pioneering logician and computer scientist best known for introducing the resolution principle, a fundamental method in automated theorem proving and logic programming.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.