Triple
T20227321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overlord Mountain |
E495419
|
entity |
| Predicate | hasPhotoView |
P49165
|
FINISHED |
| Object | visible from Whistler Blackcomb ski area |
—
|
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: visible from Whistler Blackcomb ski area | Statement: [Overlord Mountain, hasPhotoView, visible from Whistler Blackcomb ski area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotoView Context triple: [Overlord Mountain, hasPhotoView, visible from Whistler Blackcomb ski area]
-
A.
hasPhotoOn
Indicates that one entity has an associated photograph stored, displayed, or linked on another entity (such as a platform, page, or medium).
-
B.
hasPhotoFeature
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
C.
hasPhotoAppeal
Indicates that something possesses qualities that make it visually attractive or appealing in photographs.
-
D.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
E.
hasPhotoSpot
chosen
Indicates that a location or entity includes or is associated with a designated place suitable for taking photographs.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fda9428819098467e7e8c547a07 |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.