Triple
T16931618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AirAsia X |
E410721
|
entity |
| Predicate | hasLoyaltyProgram |
P178
|
FINISHED |
| Object | AirAsia Rewards |
E910494
|
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: AirAsia Rewards | Statement: [AirAsia X, hasLoyaltyProgram, AirAsia Rewards]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AirAsia Rewards Context triple: [AirAsia X, hasLoyaltyProgram, AirAsia Rewards]
-
A.
AirAsia rewards
chosen
AirAsia rewards is the frequent-flyer and customer loyalty program of AirAsia that offers members points, discounts, and exclusive benefits across flights and partner services.
-
B.
GarudaMiles
GarudaMiles is the frequent-flyer loyalty program of Garuda Indonesia, offering members mileage accrual and redemption for flights and related travel benefits.
-
C.
Asiana Club miles
Asiana Club miles are the frequent flyer reward points earned and redeemed by members of Asiana Airlines’ loyalty program for flights and partner services.
-
D.
AirAsia
AirAsia is a Malaysian low-cost airline known for its extensive network of domestic and international routes across Asia and beyond.
-
E.
KrisFlyer
KrisFlyer is the loyalty program of Singapore Airlines, allowing members to earn and redeem miles for flights, upgrades, and other travel-related rewards across the airline and its partners.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf25a6dc8190a2b9d9c4d2adc5fd |
completed | April 18, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfdeb7a88190aac21a8645607dc8 |
completed | May 10, 2026, 6:35 p.m. |
Created at: April 10, 2026, 5:30 a.m.