Triple
T36347801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Rebel Princess |
E895111
|
entity |
| Predicate | firstTelevisionStarringRoleFor |
—
|
GENERATED |
| Object | Zhang Ziyi |
—
|
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: firstTelevisionStarringRoleFor Context triple: [The Rebel Princess, firstTelevisionStarringRoleFor, Zhang Ziyi]
-
A.
portrayedInFirstTalkingRoleOf
Indicates that an entity portrayed a character in another entity’s first role in a talking (sound) production.
-
B.
screenDebutInMajorRoleFor
Indicates that one entity made their first significant on-screen appearance (major role) in a particular production or work.
-
C.
televisionRoleStart
Indicates the point in time when an entity begins performing or holding a particular role on a television production.
-
D.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
E.
televisionDebutWith
chosen
Indicates the relationship in which an entity makes its first appearance on television in association with a particular work, program, 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_69f76e4f437c8190a1af3ea2564f41f5 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:09 p.m.