Triple
T4228042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basaseachic Falls |
E94507
|
entity |
| Predicate | hasPhotographyInterest |
P49165
|
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: [Basaseachic Falls, hasPhotographyInterest, landscape photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotographyInterest Context triple: [Basaseachic Falls, hasPhotographyInterest, landscape photography]
-
A.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
B.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
C.
hasPhotoSpot
chosen
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
-
D.
hasPhotographyRestrictions
Indicates that there are specific rules or limitations governing whether and how photography is allowed.
-
E.
hasPhotographicProcess
Indicates that something is associated with, created by, or characterized through a specific photographic process or technique.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e51817c8190bff50f2c3b5deea0 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.