Triple
T26476456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 18 |
E666049
|
entity |
| Predicate | approximateHeadingDegrees |
P129753
|
FINISHED |
| Object | 180 |
—
|
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: 180 | Statement: [Runway 18, approximateHeadingDegrees, 180]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateHeadingDegrees Context triple: [Runway 18, approximateHeadingDegrees, 180]
-
A.
hasApproximateHeadingDegrees
chosen
Indicates that one entity’s heading or direction is approximately equal to a specified angle measured in degrees.
-
B.
hasApproximateHeading
Indicates that one entity’s directional heading is approximately the same as another’s, within a specified tolerance.
-
C.
approximateDirection
Indicates that one entity is located in a general or rough directional relation (e.g., roughly north, south, etc.) relative to another entity, without specifying an exact bearing.
-
D.
hasReciprocalMagneticHeadingApprox
Indicates that two entities have magnetic headings that are approximately reciprocal (differing by about 180 degrees from each other).
-
E.
hasHeadingRangeStartDegrees
Indicates the starting value, in degrees, of a specified heading or directional range.
- 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_69ee883f80dc819090e311b022b78e02 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 27, 2026, 12:23 a.m.