Jennifer Tilly
E241896
Jennifer Tilly is an American actress and poker player known for her distinctive voice and roles in films such as "Bullets Over Broadway" and the "Child's Play" horror franchise.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jennifer Tilly canonical | 17 |
How this entity was disambiguated
This entity first appeared as the object of triple T2124475 — 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: Jennifer Tilly Context triple: [Monsters, Inc., voiceCastMember, Jennifer Tilly]
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A.
Tamara Tunie
Tamara Tunie is an American actress and director best known for her long-running role as medical examiner Melinda Warner on the television series "Law & Order: Special Victims Unit."
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B.
Tyne Daly
Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
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C.
Gina Gershon
Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
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D.
Gloria Rudisch
Gloria Rudisch is an American pediatrician and public health official best known as the wife of artificial intelligence pioneer Marvin Minsky.
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E.
Jorja Fox
Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Jennifer Tilly Target entity description: Jennifer Tilly is an American actress and poker player known for her distinctive voice and roles in films such as "Bullets Over Broadway" and the "Child's Play" horror franchise.
-
A.
Tamara Tunie
Tamara Tunie is an American actress and director best known for her long-running role as medical examiner Melinda Warner on the television series "Law & Order: Special Victims Unit."
-
B.
Tyne Daly
Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
-
C.
Gina Gershon
Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
-
D.
Gloria Rudisch
Gloria Rudisch is an American pediatrician and public health official best known as the wife of artificial intelligence pioneer Marvin Minsky.
-
E.
Jorja Fox
Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
- F. None of above. chosen
Statements (50)
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: Jennifer Tilly Description of subject: Jennifer Tilly is an American actress and poker player known for her distinctive voice and roles in films such as "Bullets Over Broadway" and the "Child's Play" horror franchise.
Referenced by (17)
Full triples — surface form annotated when it differs from this entity's canonical label.