Triple
T17334249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Explorer (Flying Blue tier) |
E420893
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Flying Blue |
—
|
NE NERFINISHED |
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: Flying Blue | Statement: [Explorer (Flying Blue tier), partOf, Flying Blue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flying Blue Context triple: [Explorer (Flying Blue tier), partOf, Flying Blue]
-
A.
Flying Blue
chosen
Flying Blue is the joint frequent flyer loyalty program of Air France–KLM and partner airlines, offering members miles, elite status levels, and travel-related rewards.
-
B.
Blue Air
Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
-
C.
Flying Finn
Flying Finn is the famous nickname of Finnish middle- and long-distance runner Paavo Nurmi, one of the most dominant athletes in Olympic history.
-
D.
Flite
"Flite" is a jazz-influenced electronic track by The Cinematic Orchestra, known for its atmospheric build-up and intricate rhythmic layering.
-
E.
Airblue
Airblue is a Pakistani low-cost airline that operates domestic and international flights, with a primary base at Jinnah International Airport in Karachi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a106df48190a50f96febc13cde7 |
completed | April 19, 2026, 2:12 a.m. |
Created at: April 10, 2026, 5:43 a.m.