Triple
T28239090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 12/30 |
E711969
|
entity |
| Predicate | hasRunwayHeadingApprox |
P6272
|
FINISHED |
| Object | 120 degrees (Runway 12) |
—
|
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: 120 degrees (Runway 12) | Statement: [Runway 12/30, hasRunwayHeadingApprox, 120 degrees (Runway 12)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayHeadingApprox Context triple: [Runway 12/30, hasRunwayHeadingApprox, 120 degrees (Runway 12)]
-
A.
hasRunwayOrientation
chosen
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
hasRunwayPosition
Indicates the spatial or designated placement of an aircraft or object relative to a specific runway.
-
C.
hasRunwayApproachType
Indicates the specific type or category of approach procedure associated with a runway.
-
D.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
E.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
- 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_69efb51ece308190b8c269a057e36652 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 10:57 p.m.