Triple
T11237844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premium Laurel Class |
E265988
|
entity |
| Predicate | ticketClassCode |
P42683
|
FINISHED |
| Object | J cabin (business) fare classes |
—
|
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: J cabin (business) fare classes | Statement: [Premium Laurel Class, ticketClassCode, J cabin (business) fare classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketClassCode Context triple: [Premium Laurel Class, ticketClassCode, J cabin (business) fare classes]
-
A.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
B.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
-
C.
ticketingCode
chosen
Indicates the specific fare or booking code associated with a ticket that defines its pricing, rules, and conditions of use.
-
D.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
-
E.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e918375081908c2a7ccb50cbf331 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:30 p.m.