Triple
T27384099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 34 |
E691317
|
entity |
| Predicate | hasReciprocalHeadingApprox |
P53416
|
FINISHED |
| Object | 160 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: 160 degrees | Statement: [Runway 34, hasReciprocalHeadingApprox, 160 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReciprocalHeadingApprox Context triple: [Runway 34, hasReciprocalHeadingApprox, 160 degrees]
-
A.
hasReciprocalMagneticHeadingApprox
chosen
Indicates that two entities have magnetic headings that are approximately reciprocal (differing by about 180 degrees from each other).
-
B.
hasRelationToTrueHeading
Indicates that an entity has a specified relationship or correspondence to a true (reference) heading or direction.
-
C.
hasApproximateHeading
Indicates that one entity’s directional heading is approximately the same as another’s, within a specified tolerance.
-
D.
hasOppositeDirectionTo
Indicates that one entity’s direction is exactly reversed or opposed to the direction of another entity.
-
E.
reciprocalOrientation
Indicates that two entities are oriented toward each other in a mutually corresponding or opposite directional alignment.
- 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_69ef520386788190bc92cfcd97ebb67a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: April 27, 2026, 12:23 p.m.