Triple
T9116693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VXP |
E218737
|
entity |
| Predicate | airlineCallsign |
P13478
|
FINISHED |
| Object | AVELO |
E218738
|
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: AVELO | Statement: [VXP, airlineCallsign, AVELO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AVELO Context triple: [VXP, airlineCallsign, AVELO]
-
A.
AVELO
chosen
AVELO is the radio callsign used by Avelo Airlines, a U.S.-based low-cost carrier.
-
B.
Velo
Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
-
C.
Velous
Velous is an American producer, songwriter, and recording artist known for his work in hip-hop and R&B, including contributions to major tracks like Kanye West’s “All Day.”
-
D.
Ola Bike
Ola Bike is a bike-taxi service operated by Indian ride-hailing company Ola, providing affordable two-wheeler rides for short-distance urban travel.
-
E.
Velopark
Velopark is a cycling and sports complex in Manchester, England, known for its velodrome and related facilities that form part of the city’s wider sporting infrastructure.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8a4c9e08190ba3603a5d00afb20 |
completed | April 1, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0307299ec8190acade4f388642e23 |
completed | April 3, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:17 p.m.