Triple
T9252257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikar Airlines |
E222352
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | IKAR |
E218159
|
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: IKAR | Statement: [Ikar Airlines, callsign, IKAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IKAR Context triple: [Ikar Airlines, callsign, IKAR]
-
A.
IKAR
chosen
IKAR is the former brand name of the Russian airline now known as Pegas Fly, which operates domestic and international passenger services.
-
B.
IKA
IKA is the three-letter IATA airport code for Tehran Imam Khomeini International Airport, the main international gateway serving Tehran, Iran.
-
C.
Iken
Iken is a village in Suffolk, England, known for its ancient church and association with the Anglo-Saxon saint Botwulf (St Botolph).
-
D.
Ikire
Ikire is a prominent town in southwestern Nigeria known for its location along major transport routes and its distinctive local delicacies, particularly “dodo Ikire.”
-
E.
Kirakira
Kirakira is a small coastal town in the Solomon Islands that serves as the administrative and commercial center of Makira-Ulawa Province.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05fb1454819098f452846ca4ca61 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0780650648190bc85452678268134 |
completed | April 4, 2026, 2:31 a.m. |
Created at: March 30, 2026, 7:31 p.m.