Triple
T8491614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A359 |
E200982
|
entity |
| Predicate | aircraftRangeClass |
P57459
|
FINISHED |
| Object | long-range |
—
|
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: long-range | Statement: [A359, aircraftRangeClass, long-range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftRangeClass Context triple: [A359, aircraftRangeClass, long-range]
-
A.
aircraftCapability
Indicates that an aircraft possesses a particular capability, function, or operational feature.
-
B.
aircraftLength
Indicates the physical longitudinal measurement of an aircraft from its nose to its tail.
-
C.
flightRangeFocus
chosen
Indicates that the relationship centers on the range or distance a flight can cover, emphasizing limitations or focus on how far the flight can travel.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe55af3f48190a8cd64cdce0ebd4c |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:13 p.m.