Triple
T33499176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pehla Nasha |
E857943
|
entity |
| Predicate | featuresCameoAppearance |
—
|
GENERATED |
| Object | Aamir Khan |
—
|
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: featuresCameoAppearance Context triple: [Pehla Nasha, featuresCameoAppearance, Aamir Khan]
-
A.
featuresCameoBy
chosen
Indicates that a work includes a brief, often special-appearance role performed by the specified person or entity.
-
B.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
C.
mediaAppearanceWith
Indicates that two or more entities appeared together in the same media context, such as a show, interview, article, or broadcast.
-
D.
mediaAppearanceType
Indicates the specific kind or category of media appearance associated with an entity (e.g., interview, feature, cameo, or performance).
-
E.
appearanceInImages
Indicates that an entity is visually present or depicted within one or more images.
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:38 a.m.