Triple
T6797403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NOR SHUTTLE |
E156091
|
entity |
| Predicate | airlineTypeOfUser |
P15155
|
FINISHED |
| Object | low-cost airline |
—
|
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: low-cost airline | Statement: [NOR SHUTTLE, airlineTypeOfUser, low-cost airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineTypeOfUser Context triple: [NOR SHUTTLE, airlineTypeOfUser, low-cost airline]
-
A.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
B.
airlineCategory
chosen
Indicates the classification or type of an airline within a defined categorization system (e.g., full-service, low-cost, regional).
-
C.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
D.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
E.
ownsAirline
Indicates that one entity has legal ownership or controlling interest in an airline company.
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ca0c288190a990180fb7cfd08f |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.