Triple
T6036262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horizon Air |
E134428
|
entity |
| Predicate | frequentFlyerProgram |
P178
|
FINISHED |
| Object | Mileage Plan |
E112400
|
NE 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 Plan | Statement: [Horizon Air, frequentFlyerProgram, Mileage Plan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mileage Plan Context triple: [Horizon Air, frequentFlyerProgram, Mileage Plan]
-
A.
Mileage Plan
chosen
Mileage Plan is Alaska Airlines’ loyalty program that rewards members with miles for flights and partner activities, redeemable for travel and other benefits.
-
B.
MileagePlus
MileagePlus is United Airlines’ loyalty program that rewards members with miles and elite benefits for flying and partner activity.
-
C.
Lotusmiles
Lotusmiles is the frequent-flyer loyalty program of Vietnam Airlines, offering members mileage accrual and tiered benefits for their travel with the carrier and its partners.
-
D.
LifeMiles
LifeMiles is the frequent-flyer loyalty program of Avianca, allowing members to earn and redeem miles for flights and related travel benefits.
-
E.
Dividend Miles
Dividend Miles was the frequent-flyer loyalty program of US Airways, allowing members to earn and redeem miles for flights, upgrades, and other travel-related rewards.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b4e3ec819089b2d119ea2953fe |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1138cb2388190a80562a835388dc3 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:08 p.m.