Triple
T26914508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rapi:t α |
E677480
|
entity |
| Predicate | onboardComfort |
P121590
|
FINISHED |
| Object | reserved reclining seats |
—
|
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: reserved reclining seats | Statement: [rapi:t α, onboardComfort, reserved reclining seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onboardComfort Context triple: [rapi:t α, onboardComfort, reserved reclining seats]
-
A.
hasPassengerAmenity
chosen
Indicates that an entity provides or is equipped with a specific amenity intended for the comfort or convenience of its passengers.
-
B.
seatFeature
Indicates that a seat possesses or is equipped with a particular feature or characteristic.
-
C.
comfortLevelComparedToPremiumCabins
Indicates how the comfort level of something compares relative to that of premium cabins.
-
D.
hasLevelingSeats
Indicates that an entity is equipped with seats whose positions can be adjusted or leveled relative to their surroundings.
-
E.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
- 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_69eee9bcef1c8190be88586bb902bb9b |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61fdd39ec8190aaf1714330459136 |
completed | May 2, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:03 a.m.