Triple
T15922038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Col du Galibier |
E386114
|
entity |
| Predicate | averageGradientFromColDuLautaretApprox |
P120544
|
FINISHED |
| Object | 6.3% |
—
|
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: 6.3% | Statement: [Col du Galibier, averageGradientFromColDuLautaretApprox, 6.3%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageGradientFromColDuLautaretApprox Context triple: [Col du Galibier, averageGradientFromColDuLautaretApprox, 6.3%]
-
A.
averageGradient
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
B.
averageGradientFromOvaro
Indicates the average slope or steepness calculated starting from the location Ovaro along a specified route or segment.
-
C.
averageGradientEastSide
Indicates the average slope or rate of elevation change along the eastern side of a specified area or feature.
-
D.
usesWeightedAverageOfSlopes
Indicates that something is determined or calculated by taking a weighted average of multiple slope values.
-
E.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e172b213e481909ee0c05e16229a26 |
completed | April 16, 2026, 11:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.