Triple
T36058829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 777-200ER |
E1043019
|
entity |
| Predicate | typicalSeatingTwoClass |
—
|
GENERATED |
| Object | 314 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeatingTwoClass Context triple: [Boeing 777-200ER, typicalSeatingTwoClass, 314]
-
A.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given context.
-
B.
seatClass
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
C.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
D.
aircraftSeatingCategory
Indicates the classification of an aircraft’s seating arrangement or capacity type associated with an entity.
-
E.
classesOfSeats
Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
- F. None of above. chosen
Provenance (1 batch)
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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:08 p.m.