Triple
T7070385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bekkestua |
E164673
|
entity |
| Predicate | distanceFromOsloCentre |
P15213
|
FINISHED |
| Object | approximately 8–10 km |
—
|
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: approximately 8–10 km | Statement: [Bekkestua, distanceFromOsloCentre, approximately 8–10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromOsloCentre Context triple: [Bekkestua, distanceFromOsloCentre, approximately 8–10 km]
-
A.
distanceFromOslo
chosen
Indicates the spatial distance between a given entity’s location and the city of Oslo.
-
B.
distanceFromTrondheimApproximate
Indicates an approximate measure of how far something is from Trondheim, typically expressed as a rough or estimated distance rather than an exact value.
-
C.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
-
D.
distanceToOsloAirportGardermoen_km
Indicates the physical distance, measured in kilometers, between a given location and Oslo Airport Gardermoen.
-
E.
distanceFromLongyearbyen
Indicates the measured distance between a given location and Longyearbyen.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:39 p.m.