Triple
T20974917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro Miscanti |
E516598
|
entity |
| Predicate | scenicFor |
P41742
|
FINISHED |
| Object | high-altitude lake landscape |
—
|
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: high-altitude lake landscape | Statement: [Cerro Miscanti, scenicFor, high-altitude lake landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenicFor Context triple: [Cerro Miscanti, scenicFor, high-altitude lake landscape]
-
A.
scenicDescription
Indicates a descriptive portrayal of the visual or aesthetic qualities of a scene or landscape.
-
B.
isPartOfScenicVista
chosen
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
C.
hasScenicPassNearby
Indicates that a location is situated close to a notable scenic pass, such as a mountain or landscape viewpoint route.
-
D.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
E.
isScenicAlternativeTo
Indicates that one route, path, or option serves as an alternative to another while offering more visually appealing or picturesque surroundings.
- 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_69e0b4fee5ac8190875fa9ceba1a5e5e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fba307d88190b728544d1b6d0bb6 |
completed | April 21, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:46 p.m.