Triple
T2603817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LS |
E58608
|
entity |
| Predicate | assignedToAirline |
P41156
|
FINISHED |
| Object | Jet2 |
E8498
|
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: Jet2 | Statement: [LS, assignedToAirline, Jet2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jet2 Context triple: [LS, assignedToAirline, Jet2]
-
A.
Jet2.com
chosen
Jet2.com is a British low-cost leisure airline that operates scheduled and charter flights across Europe from multiple UK bases.
-
B.
Jet2holidays
Jet2holidays is a UK-based package holiday provider offering flights, accommodation, and transfers to popular leisure destinations, primarily served by its sister airline Jet2.com.
-
C.
easyJet
easyJet is a major British low-cost airline operating extensive domestic and European routes.
-
D.
Ryanair
Ryanair is a major Irish low-cost airline known for its extensive network of short-haul flights across Europe.
-
E.
Wizz Air
Wizz Air is a Hungarian ultra-low-cost airline known for operating an extensive network of budget flights across Europe and surrounding regions.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdd1ca0248190aa15f80b2798524e |
completed | March 7, 2026, 8:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af907ebc348190b1556a2104cba6f1 |
completed | March 10, 2026, 3:31 a.m. |
Created at: March 6, 2026, 9:49 p.m.