Triple
T9468471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Airways Concorde Room |
E228332
|
entity |
| Predicate | servesPassengerClass |
P50616
|
FINISHED |
| Object | first class |
—
|
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: first class | Statement: [British Airways Concorde Room, servesPassengerClass, first class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPassengerClass Context triple: [British Airways Concorde Room, servesPassengerClass, first class]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
seatClass
chosen
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
C.
majorPassengerService
Indicates that a transportation facility or route provides primary or significant passenger service as one of its main functions.
-
D.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
E.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
- 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fdf604481909bf7d7d477230ca3 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:53 p.m.