Triple
T4223149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Class |
E94388
|
entity |
| Predicate | bookingClassCode |
P37972
|
FINISHED |
| Object | J |
—
|
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 | Statement: [Upper Class, bookingClassCode, J]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookingClassCode Context triple: [Upper Class, bookingClassCode, J]
-
A.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
-
B.
seatClass
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
C.
ticketClass
chosen
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
D.
bookingOption
Indicates a selectable arrangement or choice available for making a booking, such as a specific time, package, or set of conditions under which a reservation can be made.
-
E.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.