Triple
T14229462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | topbonus |
E352712
|
entity |
| Predicate | membershipTier |
P35523
|
FINISHED |
| Object | topbonus Classic |
E352712
|
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: topbonus Classic | Statement: [topbonus, membershipTier, topbonus Classic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: topbonus Classic Context triple: [topbonus, membershipTier, topbonus Classic]
-
A.
topbonus
chosen
topbonus was the frequent flyer loyalty program of the former German airline Air Berlin, offering passengers mileage accrual and redemption benefits.
-
B.
EuroBonus
EuroBonus is the loyalty program of Scandinavian Airlines (SAS), offering members points, status levels, and travel-related rewards across flights and partner services.
-
C.
TOTO
TOTO is the commonly used abbreviation for the Tongue of the Ocean, a deep, U-shaped submarine trench in the Bahamas.
-
D.
Bonza
Bonza is an Australian low-cost airline known for operating domestic routes that connect regional and leisure destinations.
-
E.
Big Bet
Big Bet is a South Korean crime drama television series centered on a notorious casino kingpin in the Philippines, known for its gritty storytelling and strong performances.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622b89fc8190af08dab9e1976759 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2819bfec8190b555632338c53740 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:07 a.m.