John F. Link
E296716
John F. Link is a film editor known for his work on various Hollywood movies, including action and comedy films.
All labels observed (1)
| Label | Occurrences |
|---|---|
| John F. Link canonical | 11 |
How this entity was disambiguated
This entity first appeared as the object of triple T1200544 — 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 F. Link Context triple: [Stop! Or My Mom Will Shoot, editedBy, John F. Link]
-
A.
Alan M. Garber
Alan M. Garber is an American physician-economist and academic leader known for his work in health policy and for serving in top administrative roles at Harvard University.
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B.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
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C.
George A. Bermann
George A. Bermann is a prominent American legal scholar and expert in international and comparative law, particularly known for his work in international arbitration.
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D.
George L. Dahl
George L. Dahl was a prominent 20th-century American architect known for shaping much of Dallas’s skyline and major civic landmarks.
-
E.
James A. Abrahamson
James A. Abrahamson is a retired U.S. Air Force lieutenant general and aerospace engineer best known for directing NASA’s Space Shuttle program and leading the Strategic Defense Initiative Organization in the 1980s.
- 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 F. Link Target entity description: John F. Link is a film editor known for his work on various Hollywood movies, including action and comedy films.
-
A.
Alan M. Garber
Alan M. Garber is an American physician-economist and academic leader known for his work in health policy and for serving in top administrative roles at Harvard University.
-
B.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
C.
George A. Bermann
George A. Bermann is a prominent American legal scholar and expert in international and comparative law, particularly known for his work in international arbitration.
-
D.
George L. Dahl
George L. Dahl was a prominent 20th-century American architect known for shaping much of Dallas’s skyline and major civic landmarks.
-
E.
James A. Abrahamson
James A. Abrahamson is a retired U.S. Air Force lieutenant general and aerospace engineer best known for directing NASA’s Space Shuttle program and leading the Strategic Defense Initiative Organization in the 1980s.
- F. None of above. chosen
Statements (36)
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 F. Link Description of subject: John F. Link is a film editor known for his work on various Hollywood movies, including action and comedy films.
Referenced by (11)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Die Hard