Triple
T15760515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Børselv |
E382082
|
entity |
| Predicate | municipalityCenterDistance |
P120225
|
FINISHED |
| Object | about 40 km from Lakselv |
—
|
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 40 km from Lakselv | Statement: [Børselv, municipalityCenterDistance, about 40 km from Lakselv]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: municipalityCenterDistance Context triple: [Børselv, municipalityCenterDistance, about 40 km from Lakselv]
-
A.
nearestCityCenterDistance
Indicates the distance from a given location to the closest city center.
-
B.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
C.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
D.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
E.
nearestTownDistance
Indicates the distance from a given location to the closest town.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b52c548190a0ffa4493a4eb15c |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e03cc871d0819085c0fc54de7984ff |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 4:47 a.m.