Triple
T6964311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAW |
E161448
|
entity |
| Predicate | servesAsBaseFor |
P2421
|
FINISHED |
| Object | AJet |
E161451
|
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: AJet | Statement: [SAW, servesAsBaseFor, AJet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AJet Context triple: [SAW, servesAsBaseFor, AJet]
-
A.
AJet
chosen
AJet is a Turkish low-cost airline operating domestic and international flights, primarily associated with Sabiha Gökçen International Airport in Istanbul.
-
B.
Cargojet
Cargojet is a Canadian cargo airline specializing in time-sensitive overnight air freight services across North America and select international routes.
-
C.
Air Astra
Air Astra is a Bangladeshi airline that operates domestic flights, primarily centered around Dhaka’s Hazrat Shahjalal International Airport.
-
D.
Aero
Aero is a high-performance, sport-oriented trim level used by Saab for its 9-3 and other models, typically featuring more powerful engines and upgraded equipment.
-
E.
Avion
Avion is a commune in the Pas-de-Calais department in northern France.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daf2b7bc8190a3e73f3b24f0352b |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c758a0e5bc819098206940fc3ac623 |
completed | March 28, 2026, 4:27 a.m. |
Created at: March 27, 2026, 2:30 p.m.