Triple
T35749028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notre-Dame-de-Gravenchon |
E1033265
|
entity |
| Predicate | distanceToLeHavreKilometers |
—
|
GENERATED |
| Object | 35 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLeHavreKilometers Context triple: [Notre-Dame-de-Gravenchon, distanceToLeHavreKilometers, 35]
-
A.
distanceToLeHavre
chosen
Indicates the spatial distance between a given entity and the location of Le Havre.
-
B.
distanceFromCalais
Indicates the measured distance separating a given place or object from the location of Calais.
-
C.
distanceToToulon_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Toulon.
-
D.
distanceToRouen
Indicates the spatial distance between a given entity and the location of Rouen.
-
E.
distanceToMarseilleKilometers
Indicates the physical distance, measured in kilometers, between a given location or entity and the city of Marseille.
- F. None of above.
Provenance (1 batch)
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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:06 p.m.