Triple
T9421468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysaker Station |
E227160
|
entity |
| Predicate | distanceFromOsloS |
P15213
|
FINISHED |
| Object | 7.0 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: 7.0 km | Statement: [Lysaker Station, distanceFromOsloS, 7.0 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromOsloS Context triple: [Lysaker Station, distanceFromOsloS, 7.0 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.
distanceFromCopenhagen
Indicates the spatial distance between a given entity and the location of Copenhagen.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c2651c48190808281779fab49df |
completed | April 1, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.