Triple
T331091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City International Airport |
E6626
|
entity |
| Predicate | hubFor |
P423
|
FINISHED |
| Object | Volaris |
E45592
|
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: Volaris | Statement: [Mexico City International Airport, hubFor, Volaris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volaris Context triple: [Mexico City International Airport, hubFor, Volaris]
-
A.
Volaris
chosen
Volaris is a Mexican low-cost airline that operates domestic and international flights, primarily serving routes across Mexico, the United States, and Central America.
-
B.
Aeroméxico
Aeroméxico is Mexico’s flagship airline, operating domestic and international flights across the Americas, Europe, and Asia from its main hub in Mexico City.
-
C.
Copa Airlines
Copa Airlines is the flag carrier of Panama and a major Latin American airline known for its extensive route network centered on its hub in Panama City.
-
D.
Avelo Airlines
Avelo Airlines is a U.S. ultra-low-cost carrier known for operating point-to-point flights from secondary airports with a focus on affordability and simplicity.
-
E.
Vueling
Vueling is a Spanish low-cost airline that operates extensive domestic and European routes, particularly around major hubs such as Barcelona and other key cities.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eaafd1a48190a6d001af3c2a5318 |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f4d55d70819099ae6f963e3ed5a0 |
completed | March 1, 2026, 8:12 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.