Triple
T32069197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cars franchise |
E818964
|
entity |
| Predicate | firstFilmRelease |
—
|
GENERATED |
| Object | Cars |
—
|
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: firstFilmRelease Context triple: [Cars franchise, firstFilmRelease, Cars]
-
A.
firstFeatureFilmRelease
Indicates the date or event of an entity’s debut feature-length film being publicly released.
-
B.
firstFilmTitle
Indicates the title of the first film associated with a given entity.
-
C.
firstAppearanceFilm
Indicates the film in which an entity (such as a character or person) makes its first on-screen appearance.
-
D.
hasFirstFilm
chosen
Indicates the specific film that is recognized as the first film associated with an entity (such as a person, series, or franchise).
-
E.
firstFilmed
Indicates that one entity is the earliest or initial subject to be captured on film in relation to another entity or context.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:23 a.m.