Triple
T7619645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yavapai Point |
E172454
|
entity |
| Predicate | photographyCondition |
P42052
|
FINISHED |
| Object | good lighting at sunrise |
—
|
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: good lighting at sunrise | Statement: [Yavapai Point, photographyCondition, good lighting at sunrise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographyCondition Context triple: [Yavapai Point, photographyCondition, good lighting at sunrise]
-
A.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
B.
hasPhotographicConvention
Indicates that there is an established photographic style, rule, or convention governing how the related entities are visually represented in photographs.
-
C.
hasViewingConditions
chosen
Indicates that one entity is associated with specific viewing conditions under which it is meant to be observed or evaluated.
-
D.
conditionOfGoods
Indicates the state, quality, or integrity that the goods are in at a given time or upon a specified event.
-
E.
allowsPhotography
Indicates that one entity permits another entity to take photographs in a particular context or location.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.