Triple
T1002281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles B. Wheeler Downtown Airport |
E21629
|
entity |
| Predicate | hasHangars |
P22186
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Charles B. Wheeler Downtown Airport, hasHangars, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHangars Context triple: [Charles B. Wheeler Downtown Airport, hasHangars, true]
-
A.
hasHangarCount
Indicates the number of hangars associated with or contained by an entity.
-
B.
hasHeliport
Indicates that an entity possesses or is equipped with a heliport facility for helicopter landing and takeoff.
-
C.
hasHelipads
Indicates that an entity possesses one or more helipads available for helicopter landing and takeoff.
-
D.
hasBoardingGatesFor
Indicates that a location or facility provides designated boarding gates used for embarking passengers onto specific transportation services (such as flights or trains).
-
E.
aircraftFacility
Indicates that a facility is designed, equipped, or used to support the operation, maintenance, or accommodation of aircraft.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fcbc04819098d2125518f62ae7 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.