Triple
T13324661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Air |
E317407
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | BLUE AIR |
E317407
|
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: BLUE AIR | Statement: [Blue Air, callsign, BLUE AIR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BLUE AIR Context triple: [Blue Air, callsign, BLUE AIR]
-
A.
Blue Air
chosen
Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
-
B.
Airblue
Airblue is a Pakistani low-cost airline that operates domestic and international flights, with a primary base at Jinnah International Airport in Karachi.
-
C.
Flair Airlines
Flair Airlines is a Canadian ultra-low-cost carrier that operates domestic and select international flights, emphasizing budget-friendly travel options.
-
D.
West Air
West Air is a Chinese low-cost airline based in Chongqing that operates domestic and regional passenger services.
-
E.
Edelweiss Air
Edelweiss Air is a Swiss leisure airline based in Zurich that operates holiday and charter flights to vacation destinations worldwide.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992c1fec8190bcb6a6bb3c973a24 |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f2cd5688190a2a0db0f0295de83 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:30 p.m.