Triple
T24330080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Youngstown–Warren Regional Airport |
E613215
|
entity |
| Predicate | runway 5/23 orientation |
P6272
|
FINISHED |
| Object | 050°/230° |
—
|
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: 050°/230° | Statement: [Youngstown–Warren Regional Airport, runway 5/23 orientation, 050°/230°]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway 5/23 orientation Context triple: [Youngstown–Warren Regional Airport, runway 5/23 orientation, 050°/230°]
-
A.
hasRunwayOrientation
chosen
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
runwayFormat
Indicates the specific physical configuration or layout type of a runway used for takeoff and landing.
-
D.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
-
E.
hasRightRunwayIn25Direction
Indicates that an entity (typically an airport or airfield) possesses a right-hand runway aligned or oriented in the 25 direction.
- 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_69e2d7db6d5c819091194918157a7c1f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292f0539081908f2d1769ad122572 |
completed | April 29, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:55 a.m.