Triple
T2136599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Racetrack Playa |
E46667
|
entity |
| Predicate | photographyInterest |
P23855
|
FINISHED |
| Object | landscape photography |
—
|
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: landscape photography | Statement: [Racetrack Playa, photographyInterest, landscape photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographyInterest Context triple: [Racetrack Playa, photographyInterest, landscape photography]
-
A.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
B.
hasPhotographicSignificance
chosen
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
-
C.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
-
D.
photographer
Indicates that one entity takes photographs of another entity, typically in a professional or intentional capacity.
-
E.
captures
Indicates that one entity seizes, traps, or takes control of another entity, often preventing its escape or freedom.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbd96a3b0819081efbfef975e1513 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.