Triple
T34895759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerta de Orión |
E1006428
|
entity |
| Predicate | photographicInterest |
P23855
|
FINISHED |
| Object | night sky framing through arch |
—
|
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: night sky framing through arch | Statement: [Puerta de Orión, photographicInterest, night sky framing through arch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: photographicInterest Context triple: [Puerta de Orión, photographicInterest, night sky framing through arch]
-
A.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
B.
photographyGenre
Indicates the specific genre or style of photography that characterizes a photographic work or activity.
-
C.
hasPhotographicSignificance
chosen
Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
-
D.
usesPhotographyFrom
Indicates that one entity employs or incorporates photographic material originating from another entity.
-
E.
photographedByTourists
Indicates that the subject has been photographed by people visiting as tourists.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.