Triple
T14122792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Center |
E339943
|
entity |
| Predicate | distanceToCopenhagenAirport |
P79745
|
FINISHED |
| Object | approximately 6 kilometres |
—
|
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 6 kilometres | Statement: [Bella Center, distanceToCopenhagenAirport, approximately 6 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCopenhagenAirport Context triple: [Bella Center, distanceToCopenhagenAirport, approximately 6 kilometres]
-
A.
distanceFromCopenhagen
Indicates the spatial distance between a given entity and the location of Copenhagen.
-
B.
distanceToStockholmArlandaAirport
Indicates the measured distance between a given location or entity and Stockholm Arlanda Airport.
-
C.
distanceToOsloAirportGardermoen_km
Indicates the physical distance, measured in kilometers, between a given location and Oslo Airport Gardermoen.
-
D.
distanceFromLongyearbyen
Indicates the measured distance between a given location and Longyearbyen.
-
E.
distanceToAirport
chosen
Indicates the measured distance between a given location and the nearest or specified airport.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.