Triple
T7541441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 3 |
E178283
|
entity |
| Predicate | hasOppositeHeadingApprox |
P53416
|
FINISHED |
| Object | 210 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: 210 degrees | Statement: [Runway 3, hasOppositeHeadingApprox, 210 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOppositeHeadingApprox Context triple: [Runway 3, hasOppositeHeadingApprox, 210 degrees]
-
A.
hasApproximateHeading
Indicates that one entity’s directional heading is approximately the same as another’s, within a specified tolerance.
-
B.
hasReciprocalMagneticHeadingApprox
chosen
Indicates that two entities have magnetic headings that are approximately reciprocal (differing by about 180 degrees from each other).
-
C.
hasRelationToTrueHeading
Indicates that an entity has a specified relationship or correspondence to a true (reference) heading or direction.
-
D.
hasOppositeTime
Indicates a temporal relationship where one time point or period is positioned as the direct opposite or inverse of another within a defined temporal framework (e.g., day vs. night, past vs. future).
-
E.
isInDirectionOf
Indicates that one entity is oriented or positioned toward the direction in which another entity lies.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.