Triple
T17625288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 6/24 |
E429824
|
entity |
| Predicate | hasRunwayNumberingBasis |
P55035
|
FINISHED |
| Object | magnetic heading approximately 060°/240° |
—
|
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 approximately 060°/240° | Statement: [Runway 6/24, hasRunwayNumberingBasis, magnetic heading approximately 060°/240°]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayNumberingBasis Context triple: [Runway 6/24, hasRunwayNumberingBasis, magnetic heading approximately 060°/240°]
-
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.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dbc62e88190b9757dc7c52d7fee |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.