Triple
T38559316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | End Credits |
E928034
|
entity |
| Predicate | associatedFilmLeadActor |
—
|
GENERATED |
| Object | Leonardo DiCaprio |
—
|
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: associatedFilmLeadActor Context triple: [End Credits, associatedFilmLeadActor, Leonardo DiCaprio]
-
A.
associatedWithLeadActorOfFilm
chosen
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
B.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
C.
producedFilmStarring
Indicates that a person or company produced a film in which a specified actor or set of actors starred.
-
D.
filmLeadCharacter
Indicates that a person or character serves as the primary or central protagonist in a film.
-
E.
directorAssociatedWith
Indicates a relationship where a director is professionally connected to, responsible for, or involved with a particular entity (such as a work, organization, or project).
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:32 p.m.