Triple
T16620013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Angles ski resort |
E403799
|
entity |
| Predicate | hasSkiAreaSize |
P18014
|
FINISHED |
| Object | approximately 55 km of pistes |
—
|
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 55 km of pistes | Statement: [Les Angles ski resort, hasSkiAreaSize, approximately 55 km of pistes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSkiAreaSize Context triple: [Les Angles ski resort, hasSkiAreaSize, approximately 55 km of pistes]
-
A.
hasSkiAreaSide
Indicates that something is located on or associated with a particular side or slope of a ski area.
-
B.
hasSkiableArea
chosen
Indicates that an entity possesses an area of terrain that can be used for skiing.
-
C.
hasSkiAreaVerticalDrop
Indicates the vertical distance in elevation between the highest and lowest points of a ski area.
-
D.
hasSkiResortType
Indicates that an entity is associated with, or classified by, a specific type or category of ski resort.
-
E.
hasSkiAreaBaseElevation
Indicates the base elevation at which a ski area is situated.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754c934c8190a0a8ddd747681aa7 |
completed | April 18, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.