Triple
T27097274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Brigue |
E686338
|
entity |
| Predicate | distanceToNice |
P117026
|
FINISHED |
| Object | about 80 kilometres northeast |
—
|
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 80 kilometres northeast | Statement: [La Brigue, distanceToNice, about 80 kilometres northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNice Context triple: [La Brigue, distanceToNice, about 80 kilometres northeast]
-
A.
distanceFromNice
chosen
Indicates the spatial distance between an entity and the location referred to as Nice.
-
B.
distanceToNiceKilometers
Indicates the physical distance, measured in kilometers, between an entity and the city of Nice.
-
C.
distanceFromNiceByRoad_km
Indicates the length of the road route, in kilometers, from the city of Nice to the given location.
-
D.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
E.
distanceToNancyKilometres
Indicates the physical distance, measured in kilometers, between a given entity’s location and Nancy.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: April 27, 2026, 8:45 a.m.