Triple
T8106003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EZE |
E189226
|
entity |
| Predicate | servesAsHubFor |
P423
|
FINISHED |
| Object | JetSMART Argentina |
E100695
|
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: JetSMART Argentina | Statement: [EZE, servesAsHubFor, JetSMART Argentina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JetSMART Argentina Context triple: [EZE, servesAsHubFor, JetSMART Argentina]
-
A.
JetSMART
chosen
JetSMART is a Chilean low-cost airline operating domestic and regional flights across South America.
-
B.
Interjet
Interjet was a Mexican low-cost airline known for operating domestic and international routes across the Americas before ceasing operations in 2020.
-
C.
JetSmart Perú
JetSmart Perú is a Peruvian low-cost airline operating domestic and regional flights as part of the South American JetSmart network.
-
D.
Sky Airline
Sky Airline is a Chilean low-cost carrier that operates domestic and regional flights across South America.
-
E.
Aerolineas Argentinas
Aerolíneas Argentinas is the flag carrier airline of Argentina, operating domestic and international flights primarily from its hub in Buenos Aires.
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42f735c8819090d0d822644c0a51 |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc6422fb4c8190a5e7bedd323241d7 |
completed | April 1, 2026, 12:17 a.m. |
Created at: March 30, 2026, 5:31 p.m.