Triple
T7019905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Deux Alpes |
E162793
|
entity |
| Predicate | skiAreaElevationMax |
P75294
|
FINISHED |
| Object | approximately 3600 m |
—
|
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 3600 m | Statement: [Les Deux Alpes, skiAreaElevationMax, approximately 3600 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skiAreaElevationMax Context triple: [Les Deux Alpes, skiAreaElevationMax, approximately 3600 m]
-
A.
skiAreaName
Indicates that an entity has a specific name used to identify a ski area.
-
B.
summitElevation
Indicates the elevation or height of a summit above a reference level, typically sea level.
-
C.
isLargestSkiAreaIn
Indicates that a ski area has the greatest size (e.g., by area or extent of slopes) within the specified region or set.
-
D.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
E.
totalAscent
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
- F. None of above. chosen
Provenance (4 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e5eb904481909a900e2ba9df710b |
completed | March 27, 2026, 8:17 p.m. |
Created at: March 27, 2026, 2:34 p.m.