Triple
T3731390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 4L/22R |
E79070
|
entity |
| Predicate | hasMagneticHeadingApprox |
P30205
|
FINISHED |
| Object | 040 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: 040 degrees | Statement: [Runway 4L/22R, hasMagneticHeadingApprox, 040 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMagneticHeadingApprox Context triple: [Runway 4L/22R, hasMagneticHeadingApprox, 040 degrees]
-
A.
hasMagneticMoment
Indicates that an entity possesses a magnetic moment, characterizing the strength and orientation of its magnetism.
-
B.
hasRelationToTrueHeading
chosen
Indicates that an entity has a specified relationship or correspondence to a true (reference) heading or direction.
-
C.
magneticFieldStrength
Indicates the intensity or magnitude of a magnetic field associated with an entity or at a specific location.
-
D.
hasFieldOrientation
Indicates that one entity has a specified directional or spatial orientation relative to a field (such as magnetic, electric, or visual field).
-
E.
magneticField
Indicates the presence, strength, or configuration of a magnetic field associated with an entity or region.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb21002c81908438170ed6f6c271 |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.