Triple
T16061592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyTeam |
E389626
|
entity |
| Predicate | hasFrequentFlyerBenefit |
P13481
|
FINISHED |
| Object | mileage accrual across member airlines |
—
|
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: mileage accrual across member airlines | Statement: [SkyTeam, hasFrequentFlyerBenefit, mileage accrual across member airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequentFlyerBenefit Context triple: [SkyTeam, hasFrequentFlyerBenefit, mileage accrual across member airlines]
-
A.
associatedWithFrequentFlyerProgram
chosen
Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
-
B.
airportBenefit
Indicates that one entity gains an advantage, profit, or positive impact from the existence, operation, or services of an airport.
-
C.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
D.
hasLoyalties
Indicates that an entity feels allegiance or commitment toward one or more other entities or causes.
-
E.
fareAppliesTo
Indicates that a specific fare is applicable to a particular trip, service, passenger category, or travel condition.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:57 a.m.