Triple
T14743722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qatar Airways Privilege Club |
E346413
|
entity |
| Predicate | formerRewardCurrency |
P35525
|
FINISHED |
| Object | Qmiles |
E346410
|
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: Qmiles | Statement: [Qatar Airways Privilege Club, formerRewardCurrency, Qmiles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qmiles Context triple: [Qatar Airways Privilege Club, formerRewardCurrency, Qmiles]
-
A.
Qmiles
chosen
Qmiles are the frequent-flyer reward points earned and redeemed by members of Qatar Airways’ Privilege Club loyalty program.
-
B.
LifeMiles
LifeMiles is the frequent-flyer loyalty program of Avianca, allowing members to earn and redeem miles for flights and related travel benefits.
-
C.
ConnectMiles
ConnectMiles is the frequent-flyer loyalty program of Copa Airlines, allowing members to earn and redeem miles for flights and travel-related benefits.
-
D.
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.
-
E.
Miles&Go
Miles&Go is TAP Air Portugal’s loyalty program that allows members to earn and redeem miles for flights, upgrades, and other travel-related benefits.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7367a1c819081082cc355e385fa |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb93e94c8190beba605e26d4552c |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:30 a.m.