Triple
T11651787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airblue |
E276920
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | AIRBLUE |
E276920
|
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: AIRBLUE | Statement: [Airblue, callsign, AIRBLUE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AIRBLUE Context triple: [Airblue, callsign, AIRBLUE]
-
A.
Airblue
chosen
Airblue is a Pakistani low-cost airline that operates domestic and international flights, with a primary base at Jinnah International Airport in Karachi.
-
B.
West Air
West Air is a Chinese low-cost airline based in Chongqing that operates domestic and regional passenger services.
-
C.
Blue Air
Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
-
D.
SkyUp Airlines
SkyUp Airlines is a Ukrainian low-cost carrier known for operating domestic and international flights across Europe, the Middle East, and other regions.
-
E.
ASKY Airlines
ASKY Airlines is a West African regional airline based in Lomé, Togo, operating a network of routes across multiple countries in the region.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2d01f9c8190849f252f22519550 |
completed | April 10, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef138faf4c81908043c71550048d75 |
completed | April 27, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:39 p.m.