Triple
T38192667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laddie |
E1005513
|
entity |
| Predicate | featureActorInProminentRole |
—
|
GENERATED |
| Object | Virginia Weidler |
—
|
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: featureActorInProminentRole Context triple: [Laddie, featureActorInProminentRole, Virginia Weidler]
-
A.
leadRoleActor
Indicates that an actor performs a leading or principal role in a work or production.
-
B.
prominentAppearanceFilm
chosen
Indicates that an entity has a major or highly visible role or presence in a particular film.
-
C.
majorActor
Indicates that the subject is a primary or leading participant in the action, event, or production involving the object.
-
D.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
E.
notableCastFeature
Indicates that a cast member has a distinctive or noteworthy characteristic, role, or attribute that is especially significant in the context of the production.
- 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_69f76dbd22f48190940318cea061e8bb |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:29 p.m.