Triple
T3999623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 07L/25R |
E87182
|
entity |
| Predicate | hasReciprocalMagneticHeadingApprox |
P53416
|
FINISHED |
| Object | 250 degrees |
—
|
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: 250 degrees | Statement: [Runway 07L/25R, hasReciprocalMagneticHeadingApprox, 250 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReciprocalMagneticHeadingApprox Context triple: [Runway 07L/25R, hasReciprocalMagneticHeadingApprox, 250 degrees]
-
A.
hasRelationToTrueHeading
Indicates that an entity has a specified relationship or correspondence to a true (reference) heading or direction.
-
B.
hasApproachHeading
Indicates that an entity follows or is aligned with a specified heading or direction when making an approach.
-
C.
azimuthAccuracy
Indicates the degree of precision or allowable error in the measured or specified azimuth angle between entities.
-
D.
hasNavigationAid
Indicates that one entity provides or is equipped with a navigation aid used to assist in determining position or direction.
-
E.
containsDirectionOf
Indicates that one entity includes or encompasses the directional orientation or path associated with another entity.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:34 p.m.