Triple
T7019906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Deux Alpes |
E162793
|
entity |
| Predicate | skiAreaElevationMin |
P35776
|
FINISHED |
| Object | approximately 1300 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 1300 m | Statement: [Les Deux Alpes, skiAreaElevationMin, approximately 1300 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skiAreaElevationMin Context triple: [Les Deux Alpes, skiAreaElevationMin, approximately 1300 m]
-
A.
skiAreaName
Indicates that an entity has a specific name used to identify a ski area.
-
B.
elevationMinM
Indicates the minimum elevation, measured in meters, at which an entity or phenomenon occurs or is situated.
-
C.
elevationMinApprox
chosen
Indicates an approximate value for the minimum elevation associated with an entity or location.
-
D.
skiAreaType
Indicates the specific type or classification of a ski area associated with an entity (e.g., resort, backcountry, terrain park).
-
E.
elevationMinFeet
Indicates the minimum elevation of an entity or location, measured in feet.
- 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_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. |
Created at: March 27, 2026, 2:34 p.m.