Triple
T10753150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singapore–New York (ultra-long-haul) |
E253620
|
entity |
| Predicate | hasCabinConfiguration |
P16894
|
FINISHED |
| Object | business 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: business class | Statement: [Singapore–New York (ultra-long-haul), hasCabinConfiguration, business class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCabinConfiguration Context triple: [Singapore–New York (ultra-long-haul), hasCabinConfiguration, business class]
-
A.
cabinConfiguration
chosen
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
B.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
C.
hasCabins
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
-
D.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
-
E.
cabinTypes
Indicates the types or categories of cabins associated with an entity, such as the different classes or configurations available.
- 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_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. |
Created at: April 8, 2026, 9:15 p.m.