Triple
T6273105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vágar Airport |
E140585
|
entity |
| Predicate | distance to Tórshavn (kilometers) |
P69089
|
FINISHED |
| Object | about 47 |
—
|
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 47 | Statement: [Vágar Airport, distance to Tórshavn (kilometers), about 47]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distance to Tórshavn (kilometers) Context triple: [Vágar Airport, distance to Tórshavn (kilometers), about 47]
-
A.
distanceToLerwickKilometers
Indicates the physical distance, measured in kilometers, between a given entity’s location and the town of Lerwick.
-
B.
distanceFromCopenhagen
Indicates the spatial distance between a given entity and the location of Copenhagen.
-
C.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
-
D.
distanceFromTallinn
Indicates the measured distance between a given place or object and the city of Tallinn.
-
E.
distanceFromOslo
Indicates the spatial distance between a given entity’s location and the city of Oslo.
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063be5a148190a8752426d2d220f8 |
completed | March 22, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69c05606fb50819082d1a5a91e5030b6 |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056c965ac8190b938502fa8c74e1b |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:25 p.m.