Triple
T3471920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warrenton–Fauquier Airport |
E73279
|
entity |
| Predicate | isCommercialServiceAirport |
P49167
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Warrenton–Fauquier Airport, isCommercialServiceAirport, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommercialServiceAirport Context triple: [Warrenton–Fauquier Airport, isCommercialServiceAirport, no]
-
A.
isOnlyCommercialAirportIn
Indicates that an airport is the sole commercial airport serving a specified geographic area or region.
-
B.
isPublicAirport
Indicates that an airport is open for use by the general public rather than restricted to private or military operations.
-
C.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
D.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
E.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3cc8488190b97c732e3f600a90 |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:17 p.m.