Triple
T7786267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enköping |
E187251
|
entity |
| Predicate | roadDistanceToArlandaAirport |
P69991
|
FINISHED |
| Object | about 70 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: about 70 km | Statement: [Enköping, roadDistanceToArlandaAirport, about 70 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToArlandaAirport Context triple: [Enköping, roadDistanceToArlandaAirport, about 70 km]
-
A.
distanceToStockholmArlandaAirport
chosen
Indicates the measured distance between a given location or entity and Stockholm Arlanda Airport.
-
B.
distanceToOsloAirportGardermoen_km
Indicates the physical distance, measured in kilometers, between a given location and Oslo Airport Gardermoen.
-
C.
distanceFromStockholmCityCentre
Indicates the measured distance between a given location and the center of Stockholm city.
-
D.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
-
E.
distanceFromUppsala_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Uppsala.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 4:23 p.m.