Triple
T12531738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3 |
E299583
|
entity |
| Predicate | associatedWithAirlineType |
P73988
|
FINISHED |
| Object | largest Greek 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: largest Greek airline | Statement: [A3, associatedWithAirlineType, largest Greek airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAirlineType Context triple: [A3, associatedWithAirlineType, largest Greek airline]
-
A.
associatedAirlineType
chosen
Indicates a relationship where an airline is linked to a specific classification or type (e.g., carrier category or operational class).
-
B.
associatedAirlineServiceType
Indicates the specific type or category of airline service that is linked or related to another entity or activity.
-
C.
associatedWithIATAAirlineCode
Indicates that an entity is linked to or identified by a specific IATA airline code.
-
D.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
E.
associatedWithAirlineOperations
Indicates a relationship in which an entity is connected to, involved in, or relevant to the operations and activities of an 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.