Peter Gallagher
E256071
Peter Gallagher is an American actor and singer known for his work in film, television, and theater, including prominent roles in "The O.C.," "Sex, Lies, and Videotape," and numerous Broadway productions.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Peter Gallagher canonical | 12 |
| Dan Gallagher | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2289817 — 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: Peter Gallagher Context triple: [Burlesque, castMember, Peter Gallagher]
-
A.
Michael Barrett
Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
-
B.
Andrew Duggan
Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
-
C.
Michael Callaghan
Michael Callaghan is one of the children of former UK Prime Minister James Callaghan.
-
D.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
E.
Tony McCarroll
Tony McCarroll is an English drummer best known as the original drummer for the rock band Oasis, playing on their debut album "Definitely Maybe."
- 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: Peter Gallagher Target entity description: Peter Gallagher is an American actor and singer known for his work in film, television, and theater, including prominent roles in "The O.C.," "Sex, Lies, and Videotape," and numerous Broadway productions.
-
A.
Michael Barrett
Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
-
B.
Andrew Duggan
Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
-
C.
Michael Callaghan
Michael Callaghan is one of the children of former UK Prime Minister James Callaghan.
-
D.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
-
E.
Tony McCarroll
Tony McCarroll is an English drummer best known as the original drummer for the rock band Oasis, playing on their debut album "Definitely Maybe."
- F. None of above. chosen
Statements (45)
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: Peter Gallagher Description of subject: Peter Gallagher is an American actor and singer known for his work in film, television, and theater, including prominent roles in "The O.C.," "Sex, Lies, and Videotape," and numerous Broadway productions.
Referenced by (13)
Full triples — surface form annotated when it differs from this entity's canonical label.