Triple
T3471903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warrenton–Fauquier Airport |
E73279
|
entity |
| Predicate | hasFixed-base operator |
P22187
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Warrenton–Fauquier Airport, hasFixed-base operator, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFixed-base operator Context triple: [Warrenton–Fauquier Airport, hasFixed-base operator, yes]
-
A.
hasFixedBaseOperator
chosen
Indicates that an entity is associated with or utilizes a specific, non-changing base operator as part of its definition or behavior.
-
B.
operatesBase
Indicates that an organization or agent runs or manages a primary facility, location, or base of operations.
-
C.
fixedBy
Indicates that one entity is repaired, corrected, or resolved through the action or intervention of another entity.
-
D.
hasOriginalOperator
Indicates that an entity is associated with the operator that originally created, owned, or controlled it.
-
E.
operatorVariant
Indicates a relationship where one operator is an alternative or modified form of another, typically differing in implementation, configuration, or usage while serving a related function.
- 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_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. |
Created at: March 8, 2026, 3:17 p.m.