Triple
T24321437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter O. Knight Airport |
E612972
|
entity |
| Predicate | distanceFromDowntown (kilometers) |
P1299
|
FINISHED |
| Object | approximately 5 |
—
|
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 5 | Statement: [Peter O. Knight Airport, distanceFromDowntown (kilometers), approximately 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDowntown (kilometers) Context triple: [Peter O. Knight Airport, distanceFromDowntown (kilometers), approximately 5]
-
A.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
B.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
C.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
-
D.
distanceFromMajorCity
Indicates the measured distance between a given location and a specified major city.
-
E.
distanceFromNearestSettlementKilometers
Indicates the distance, measured in kilometers, from an entity’s location to the closest human settlement.
- 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_69e2d7da491c8190b6e6218af50923db |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292ac7fc08190993f707f2f97e7f5 |
completed | April 29, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f1c45f45888190a9ccc225906c34bd |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:51 a.m.