Triple
T36347521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziyi |
E895105
|
entity |
| Predicate | associatedProfessionOfNotableBearer |
P35215
|
FINISHED |
| Object | acting |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: acting | Statement: [Ziyi, associatedProfessionOfNotableBearer, acting]
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 (3 batches)
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. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.