Triple
T38121429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerler |
E951946
|
entity |
| Predicate | skiResortTopElevation |
P75294
|
FINISHED |
| Object | approximately 2630 meters above sea level |
—
|
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: approximately 2630 meters above sea level | Statement: [Cerler, skiResortTopElevation, approximately 2630 meters above sea level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skiResortTopElevation Context triple: [Cerler, skiResortTopElevation, approximately 2630 meters above sea level]
-
A.
skiAreaElevationMax
chosen
Indicates the maximum elevation, typically in meters or feet, reached within a ski area.
-
B.
hasSkiAreaBaseElevation
Indicates the base elevation at which a ski area is situated.
-
C.
peakElevationMetres
Indicates the maximum height of an entity above sea level, measured in metres.
-
D.
skiAreaAltitudeRange_m
Indicates the range of altitudes, in meters, over which a ski area extends.
-
E.
summitSnowline
Indicates the elevation or position on a mountain where snow persists at or near the summit.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.