Michael Jenning
E1043053
Michael Jenning is a screenwriter known for his work on the film "Next of Kin."
All labels observed (1)
| Label | Occurrences |
|---|---|
| Michael Jenning canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13481280 — 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: Michael Jenning Context triple: [Next of Kin, screenwriter, Michael Jenning]
-
A.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
B.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
C.
Michael Kinney
Michael Kinney is a relatively obscure individual whose primary distinguishing feature is sharing the surname Kinney, with no widely recognized public achievements or roles documented.
-
D.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
E.
Luke Jennings
Luke Jennings is a British author and former dance critic best known for creating the Villanelle novels that inspired the television series "Killing Eve."
- 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: Michael Jenning Target entity description: Michael Jenning is a screenwriter known for his work on the film "Next of Kin."
-
A.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
B.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
C.
Michael Kinney
Michael Kinney is a relatively obscure individual whose primary distinguishing feature is sharing the surname Kinney, with no widely recognized public achievements or roles documented.
-
D.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
E.
Luke Jennings
Luke Jennings is a British author and former dance critic best known for creating the Villanelle novels that inspired the television series "Killing Eve."
- F. None of above. chosen
Statements (7)
| Predicate | Object |
|---|---|
| instanceOf |
film
ⓘ
person ⓘ |
| countryOfCitizenship |
United States of America
ⓘ
surface form:
United States
|
| knownFor | Next of Kin NERFINISHED ⓘ |
| occupation | screenwriter ⓘ |
| screenwriter | Michael Jenning NERFINISHED ⓘ |
| work | Next of Kin 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.
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: Michael Jenning Description of subject: Michael Jenning is a screenwriter known for his work on the film "Next of Kin."
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.