Triple
T36217646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Col d’Aubisque |
E1047742
|
entity |
| Predicate | averageGradientFromLaruns |
P186506
|
FINISHED |
| Object | 7.2 % |
—
|
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: 7.2 % | Statement: [Col d’Aubisque, averageGradientFromLaruns, 7.2 %]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageGradientFromLaruns Context triple: [Col d’Aubisque, averageGradientFromLaruns, 7.2 %]
-
A.
averageGradient
Indicates the mean rate of change (slope) of a quantity over a specified interval or region.
-
B.
averageGradientFromJausiers
Indicates the average gradient (slope) calculated from the location or point of reference named Jausiers to another point or along a specified route.
-
C.
averageGradientFromColDuLautaretApprox
Indicates the approximate average gradient (slope) calculated from the Col du Lautaret over a specified segment or route.
-
D.
averageGradientFromValloireApprox
Indicates the approximate average gradient measured from the location or point referred to as Valloire.
-
E.
averageGradientFromOvaro
Indicates the average slope or steepness calculated starting from the location Ovaro along a specified route or segment.
- 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_69f76e42c878819095c8d19c0267fb87 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:09 p.m.