Triple
T11158033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wingo |
E263961
|
entity |
| Predicate | parentCompany |
P254
|
FINISHED |
| Object | Copa Airlines Colombia |
E45992
|
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: Copa Airlines Colombia | Statement: [Wingo, parentCompany, Copa Airlines Colombia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Copa Airlines Colombia Context triple: [Wingo, parentCompany, Copa Airlines Colombia]
-
A.
Copa Airlines
chosen
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.
-
B.
Viva Air Colombia
Viva Air Colombia was a Colombian low-cost airline known for operating domestic and regional flights across Latin America.
-
C.
Condor Airlines
Condor Airlines is a German leisure airline that primarily operates holiday flights from Germany to vacation destinations worldwide.
-
D.
Avianca
Avianca is Colombia’s flagship airline and one of Latin America’s largest carriers, operating an extensive domestic and international route network.
-
E.
Boliviana de Aviación
Boliviana de Aviación is Bolivia’s state-owned flag carrier airline, operating domestic and international passenger and cargo services.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e87fe9a881909540ecc4ed9b6b9f |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4aced563c8190a56ab5ff0618d21f |
completed | April 19, 2026, 10:22 a.m. |
Created at: April 8, 2026, 9:28 p.m.