Triple
T36347521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziyi |
E895105
|
entity |
| Predicate | associatedProfessionOfNotableBearer |
—
|
GENERATED |
| Object | acting |
—
|
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: associatedProfessionOfNotableBearer Context triple: [Ziyi, associatedProfessionOfNotableBearer, acting]
-
A.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
B.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
C.
associatedWithArtHistoricalRoleOfNotableBearer
Indicates a relationship where an entity is linked to the specific art-historical role or function held by a notable individual.
-
D.
isAssociatedWithProfessionOfBearer
chosen
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
E.
notableBearerOfRole
Indicates that an entity is a particularly prominent or well-known holder or performer of a specified role.
- 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.