Triple
T16243790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storslett |
E394316
|
entity |
| Predicate | distanceToTromsø_km |
P122312
|
FINISHED |
| Object | about 160 |
—
|
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 160 | Statement: [Storslett, distanceToTromsø_km, about 160]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTromsø_km Context triple: [Storslett, distanceToTromsø_km, about 160]
-
A.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
-
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.
distanceFromOslo
Indicates the spatial distance between a given entity’s location and the city of Oslo.
-
D.
distanceFromBodø
Indicates the spatial distance between a given entity and the location of Bodø.
-
E.
distanceFromStavanger
Indicates the spatial distance between a given entity or location and the city of Stavanger.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24560060c8190ace4f4c0bd0d886d |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:04 a.m.