Triple
T10753152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singapore–New York (ultra-long-haul) |
E253620
|
entity |
| Predicate | doesNotOfferCabinClass |
P95795
|
FINISHED |
| Object | regular economy 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: regular economy class | Statement: [Singapore–New York (ultra-long-haul), doesNotOfferCabinClass, regular economy class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotOfferCabinClass Context triple: [Singapore–New York (ultra-long-haul), doesNotOfferCabinClass, regular economy class]
-
A.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
C.
hasCabins
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
-
D.
isPassengerOnly
Indicates that the subject entity is restricted to passenger use only and does not accommodate cargo, freight, or mixed-use purposes.
-
E.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
- F. None of above. chosen
Provenance (4 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dc2543c8190bb060aa7a1fed6a6 |
completed | April 9, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:15 p.m.