Triple
T17756197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digne-les-Bains |
E443245
|
entity |
| Predicate | distanceFromNiceKm |
P117025
|
FINISHED |
| Object | about 150 |
—
|
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: about 150 | Statement: [Digne-les-Bains, distanceFromNiceKm, about 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNiceKm Context triple: [Digne-les-Bains, distanceFromNiceKm, about 150]
-
A.
distanceFromNiceByRoad_km
Indicates the length of the road route, in kilometers, from the city of Nice to the given location.
-
B.
distanceFromNice
Indicates the spatial distance between an entity and the location referred to as Nice.
-
C.
distanceToNiceKilometers
chosen
Indicates the physical distance, measured in kilometers, between an entity and the city of Nice.
-
D.
distanceFromFoixKilometres
Indicates the physical distance, measured in kilometers, between a given place or entity and the location of Foix.
-
E.
distanceFromBesançonKilometres
Indicates the distance, measured in kilometers, between an entity and the city of Besançon.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841f29f08190b1a1e9624d88120f |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.