Triple
T33308951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar (album) |
E852814
|
entity |
| Predicate | mainPerformerFormerOccupation |
P107616
|
FINISHED |
| Object | fashion model |
—
|
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: fashion model | Statement: [Sugar (album), mainPerformerFormerOccupation, fashion model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPerformerFormerOccupation Context triple: [Sugar (album), mainPerformerFormerOccupation, fashion model]
-
A.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
memberLaterOccupation
Indicates that an individual later held a particular occupation or position after an earlier point in time or role.
-
D.
economicRolePast
Indicates that an entity previously held a specific economic function, position, or role in the past.
-
E.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
- 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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: May 1, 2026, 1:33 a.m.