Triple
T26656238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aire-sur-l’Adour |
E666513
|
entity |
| Predicate | distanceToPauKmApprox |
P197546
|
FINISHED |
| Object | 60 |
—
|
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: 60 | Statement: [Aire-sur-l’Adour, distanceToPauKmApprox, 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPauKmApprox Context triple: [Aire-sur-l’Adour, distanceToPauKmApprox, 60]
-
A.
distanceToLePuy-en-Velay
Indicates the spatial distance between a given entity and the location of Le Puy-en-Velay.
-
B.
distanceFromFoixKilometres
Indicates the physical distance, measured in kilometers, between a given place or entity and the location of Foix.
-
C.
distanceFromNiceByRoad_km
Indicates the length of the road route, in kilometers, from the city of Nice to the given location.
-
D.
distanceToÉpinalKilometres
Indicates the physical distance, measured in kilometers, between a given place or entity and the location of Épinal.
-
E.
distanceToPontDuGard
Indicates the measured spatial distance between a given entity and the Pont du Gard.
- 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_69ee9cf8c7188190b9b00270a8a89164 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
| PDg | Predicate description generation | batch_69fe9b013ec481908f89beddb9c4cd4e |
completed | May 9, 2026, 2:25 a.m. |
Created at: April 27, 2026, 2:35 a.m.