Triple
T38671149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libra Films International |
E940591
|
entity |
| Predicate | typeOfFilmsHandled |
—
|
GENERATED |
| Object | foreign-language films |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfFilmsHandled Context triple: [Libra Films International, typeOfFilmsHandled, foreign-language films]
-
A.
workFilmType
chosen
Indicates the type or category of film associated with a particular work.
-
B.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
C.
cinemaType
Indicates the specific category or kind of cinema associated with an entity (e.g., multiplex, art house, drive-in).
-
D.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
E.
distributedFilmType
Indicates that a film was distributed in a particular format or category of distribution.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:33 p.m.