Triple
T27176065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherie Berry |
E683045
|
entity |
| Predicate | hasPhotoDisplayedIn |
P66522
|
FINISHED |
| Object | elevators in North Carolina |
—
|
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: elevators in North Carolina | Statement: [Cherie Berry, hasPhotoDisplayedIn, elevators in North Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotoDisplayedIn Context triple: [Cherie Berry, hasPhotoDisplayedIn, elevators in North Carolina]
-
A.
hasPhotoOn
chosen
Indicates that one entity has an associated photograph stored, displayed, or linked on another entity (such as a platform, page, or medium).
-
B.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
C.
hasPhotographBy
Indicates that an entity is depicted in or associated with a photograph that was created or taken by a specified photographer.
-
D.
hasPhotoAppeal
Indicates that something possesses qualities that make it visually attractive or appealing in photographs.
-
E.
hasPhotographs
Indicates that one entity possesses, contains, or is associated with one or more photographs of another entity or subject.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 9:26 a.m.