Triple
T27449649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 07/25 |
E692397
|
entity |
| Predicate | hasRunwayNumberingBasedOn |
P55035
|
FINISHED |
| Object | magnetic heading |
—
|
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: magnetic heading | Statement: [Runway 07/25, hasRunwayNumberingBasedOn, magnetic heading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayNumberingBasedOn Context triple: [Runway 07/25, hasRunwayNumberingBasedOn, magnetic heading]
-
A.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
B.
usesRunwayNumberingConvention
chosen
Indicates that an airport or runway follows a specific standardized system for assigning runway identification numbers.
-
C.
hasRunwayDesignationSide
Indicates that a runway designation is associated with a specific side or direction of the runway (e.g., left, right, or center).
-
D.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
E.
hasRunwayDesignatorType
Indicates the specific type or classification of a runway’s designator used to identify that runway.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 12:47 p.m.