Triple
T32156177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alain-Fabien Delon |
E821296
|
entity |
| Predicate | hasPhotographicAppearanceIn |
P179954
|
FINISHED |
| Object | fashion magazines |
—
|
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 magazines | Statement: [Alain-Fabien Delon, hasPhotographicAppearanceIn, fashion magazines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotographicAppearanceIn Context triple: [Alain-Fabien Delon, hasPhotographicAppearanceIn, fashion magazines]
-
A.
photographicAppearance
Indicates that one entity visually appears in a photograph or photographic representation of another entity.
-
B.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
C.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
D.
hasPhotographAt
Indicates that a photograph depicting an entity was taken or exists at a specific location or event.
-
E.
hasPhotographBy
Indicates that an entity is depicted in or associated with a photograph that was created or taken by a specified photographer.
- F. None of above. chosen
Provenance (4 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
| PDg | Predicate description generation | batch_69f72920c6208190aa4aba6cb6193109 |
completed | May 3, 2026, 10:53 a.m. |
Created at: May 1, 2026, 12:32 a.m.