Audrey Billings
E847871
Audrey Billings is a supporting character in the action film "Transporter 2," involved in the high-stakes kidnapping plot that drives the movie’s narrative.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Audrey Billings canonical | 1 |
Statements (15)
| Predicate | Object |
|---|---|
| instanceOf |
fictional character
ⓘ
film character ⓘ |
| appearsIn | Transporter 2 NERFINISHED ⓘ |
| countryOfOriginOfWork |
United States of America
ⓘ
surface form:
United States
|
| genreOfWorkAppearedIn |
action
ⓘ
crime ⓘ thriller ⓘ |
| hasFictionalUniverse | Transporter universe NERFINISHED ⓘ |
| involvedIn | kidnapping plot in Transporter 2 ⓘ |
| medium | film ⓘ |
| narrativeFunction | kidnapping plot participant ⓘ |
| partOfFranchise | Transporter film series NERFINISHED ⓘ |
| roleInWork | supporting character ⓘ |
| workType | action film ⓘ |
| yearOfWorkRelease | 2005 ⓘ |
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: Audrey Billings Description of subject: Audrey Billings is a supporting character in the action film "Transporter 2," involved in the high-stakes kidnapping plot that drives the movie’s narrative.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.