Triple
T18986864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namunukula mountain range |
E464578
|
entity |
| Predicate | hasPhotogenicQuality |
P121927
|
FINISHED |
| Object | sunrise views |
—
|
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: sunrise views | Statement: [Namunukula mountain range, hasPhotogenicQuality, sunrise views]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotogenicQuality Context triple: [Namunukula mountain range, hasPhotogenicQuality, sunrise views]
-
A.
hasPhotogenicFeature
chosen
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
B.
hasPhotoFeature
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
C.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
D.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
-
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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d660835c8190bedd78590b3e0a7e |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f88e0c81908cb20f08bf24cd32 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.