Triple
T23554055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Cunningham |
E578129
|
entity |
| Predicate | photographyFocus |
P62927
|
FINISHED |
| Object | everyday people’s clothing and style |
—
|
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: everyday people’s clothing and style | Statement: [Bill Cunningham, photographyFocus, everyday people’s clothing and style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographyFocus Context triple: [Bill Cunningham, photographyFocus, everyday people’s clothing and style]
-
A.
photographyGenre
chosen
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
B.
poseFocus
Indicates that attention or emphasis is directed toward a particular pose or body position within a scene or interaction.
-
C.
usesPhotographyFrom
Indicates that one entity employs or incorporates photographic material originating from another entity.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
photographer
Indicates that one entity takes photographs of another entity, typically in a professional or intentional capacity.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed17fc881908b45dcde14790d42 |
completed | April 29, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:12 p.m.