Triple
T26025227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LJ |
E647269
|
entity |
| Predicate | airlineOperatingModel |
P134019
|
FINISHED |
| Object | low-cost |
—
|
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 | Statement: [LJ, airlineOperatingModel, low-cost]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineOperatingModel Context triple: [LJ, airlineOperatingModel, low-cost]
-
A.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
B.
airlineServiceModel
chosen
Indicates a relationship where an airline operates according to, or is characterized by, a particular service model (such as full-service, low-cost, or hybrid).
-
C.
airlineOperator
Indicates that one entity operates or manages airline services for another entity or in a specified context.
-
D.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
E.
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.
- 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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 22, 2026, 9:05 a.m.