Triple
T10810578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert |
E255088
|
entity |
| Predicate | notableBearerProfession |
P13522
|
FINISHED |
| Object | film actor |
—
|
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: film actor | Statement: [Albert, notableBearerProfession, film actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableBearerProfession Context triple: [Albert, notableBearerProfession, film actor]
-
A.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
B.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
C.
notableCharacterOccupation
Indicates that a notable character is associated with a specific occupation or professional role.
-
D.
hasNotableBearerOccupation
chosen
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
E.
notableBearerFullName
Indicates that a full personal name is that of a notable or well-known bearer associated with the referenced entity.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b6efc48190bb64b5a8fac843c4 |
completed | April 9, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.