Triple
T34394866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suites (Singapore Airlines) |
E882801
|
entity |
| Predicate | bookingClassCodeCategory |
P37972
|
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: [Suites (Singapore Airlines), bookingClassCodeCategory, first class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookingClassCodeCategory Context triple: [Suites (Singapore Airlines), bookingClassCodeCategory, first class]
-
A.
bookingCodeType
Indicates the type or category of a booking code used to classify or identify a reservation.
-
B.
reservationCategory
Indicates the classification or type assigned to a reservation (such as its purpose, priority, or usage group) within a system.
-
C.
ticketClass
chosen
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
D.
airlineClass
Indicates the specific travel class or service level assigned to a passenger or ticket on an airline flight.
-
E.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:59 a.m.