Damien LeVeck
E469231
Damien LeVeck is a film editor and director known for his work in genre and independent cinema.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Damien LeVeck canonical | 1 |
Statements (39)
| Predicate | Object |
|---|---|
| instanceOf |
film director
ⓘ
film editor ⓘ person ⓘ |
| activeInField |
film industry
ⓘ
television ⓘ |
| basedOn | The Cleansing Hour (short film) NERFINISHED ⓘ |
| basedOnWorkAdaptedTo | The Cleansing Hour (feature film) NERFINISHED ⓘ |
| countryOfCitizenship | United States of America ⓘ |
| directorOf |
The Cleansing Hour (feature film)
NERFINISHED
ⓘ
The Cleansing Hour (short film) NERFINISHED ⓘ |
| editorOf |
The Cleansing Hour (feature film)
NERFINISHED
ⓘ
The Cleansing Hour (short film) NERFINISHED ⓘ |
| filmFestivalScreening |
Bucheon International Fantastic Film Festival
NERFINISHED
ⓘ
Fantastic Fest NERFINISHED ⓘ Screamfest Horror Film Festival NERFINISHED ⓘ Sitges Film Festival NERFINISHED ⓘ |
| genre |
horror film
ⓘ
independent film ⓘ thriller film ⓘ |
| hasRole |
director
ⓘ
editor ⓘ writer ⓘ |
| industry |
independent film industry
ⓘ
motion picture industry ⓘ |
| knownFor |
genre cinema
ⓘ
independent cinema ⓘ |
| languageOfWorkOrName | English ⓘ |
| notableAward |
Screamfest Horror Film Festival award for Best Director (short film) for The Cleansing Hour
NERFINISHED
ⓘ
Screamfest Horror Film Festival award for Best Editing (short film) for The Cleansing Hour NERFINISHED ⓘ |
| notableFor |
combining practical effects with digital effects in horror filmmaking
ⓘ
exploring themes of faith and media exploitation in horror ⓘ |
| notableWork |
The Cleansing Hour
NERFINISHED
ⓘ
The Cleansing Hour (feature film) NERFINISHED ⓘ The Cleansing Hour (short film) NERFINISHED ⓘ |
| occupation |
film director
ⓘ
film editor ⓘ screenwriter ⓘ |
| workAdaptedAs | The Cleansing Hour (feature film adaptation of short) NERFINISHED ⓘ |
| workLocation | Los Angeles ⓘ |
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: Damien LeVeck Description of subject: Damien LeVeck is a film editor and director known for his work in genre and independent cinema.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Gully