Triple
T3885716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean John |
E92934
|
entity |
| Predicate | hasCelebrityClientele |
P33576
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sean John, hasCelebrityClientele, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCelebrityClientele Context triple: [Sean John, hasCelebrityClientele, yes]
-
A.
hasNotablePersonRaisedHere
Indicates that a notable person spent their formative or upbringing years in the referenced place.
-
B.
hasNotablePersonAsFace
Indicates that an entity is publicly represented or symbolized by a specific notable person, such as a spokesperson, ambassador, or brand face.
-
C.
hasCustomers
chosen
Indicates that an entity maintains a business relationship in which other entities purchase or receive its goods or services as customers.
-
D.
hasAudienceReception
Indicates the relationship between a work or event and how it is received, perceived, or evaluated by its audience.
-
E.
hasEntertainmentVenue
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec942bfc8190a398fe370715a28b |
completed | March 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69aee759609c8190985e96ec6d96dedd |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.