Triple
T24216652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Lagoon |
E601322
|
entity |
| Predicate | distanceFromKeflavíkAirport |
P155228
|
FINISHED |
| Object | approximately 20 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: approximately 20 km | Statement: [Blue Lagoon, distanceFromKeflavíkAirport, approximately 20 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKeflavíkAirport Context triple: [Blue Lagoon, distanceFromKeflavíkAirport, approximately 20 km]
-
A.
distanceFromReykjavík
Indicates the spatial distance between an entity’s location and the city of Reykjavík.
-
B.
distanceToStockholmArlandaAirport
Indicates the measured distance between a given location or entity and Stockholm Arlanda Airport.
-
C.
distance to Tórshavn (kilometers)
Indicates the length, in kilometers, of the shortest travel distance between an entity and the location Tórshavn.
-
D.
distanceToOsloAirportGardermoen_km
Indicates the physical distance, measured in kilometers, between a given location and Oslo Airport Gardermoen.
-
E.
distanceFromTallinn
Indicates the measured distance between a given place or object and the city of Tallinn.
- 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_69e29537ca548190b94a37ebe1977caf |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f28208d87081909b32c84328b8f3ba |
completed | April 29, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 17, 2026, 11:58 p.m.