Triple
T13278733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chairman’s Preferred |
E316260
|
entity |
| Predicate | checkInClassOfServicePriority |
P50616
|
FINISHED |
| Object | equivalent to premium cabin |
—
|
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: equivalent to premium cabin | Statement: [Chairman’s Preferred, checkInClassOfServicePriority, equivalent to premium cabin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: checkInClassOfServicePriority Context triple: [Chairman’s Preferred, checkInClassOfServicePriority, equivalent to premium cabin]
-
A.
hasPrioritySeating
Indicates that one entity provides or designates reserved or preferential seating for another entity.
-
B.
seatClass
chosen
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
C.
typeOfPriority
Indicates the specific priority level or category assigned to something relative to other items or tasks.
-
D.
ticketClassSystem
Indicates that an entity is classified within a particular ticketing or fare class system that defines categories or levels of tickets.
-
E.
serviceNumberOrClass
Indicates that one entity specifies the service identifier or class designation associated with another entity.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:26 p.m.