Triple
T280847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Class (Delta Air Lines) |
E5349
|
entity |
| Predicate | typicalSeatConfiguration |
P5253
|
FINISHED |
| Object | 2‑2 on narrow‑body aircraft |
—
|
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: 2‑2 on narrow‑body aircraft | Statement: [First Class (Delta Air Lines), typicalSeatConfiguration, 2‑2 on narrow‑body aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeatConfiguration Context triple: [First Class (Delta Air Lines), typicalSeatConfiguration, 2‑2 on narrow‑body aircraft]
-
A.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
D.
hasClubSeats
Indicates that an entity (such as a venue or section) includes or is equipped with club-level seating.
-
E.
vehicleLayout
chosen
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e0868708190ad551ca06cc57f4a |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b765f488190b2cbe4b45cd42821 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.