Triple
T34006807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KBLV |
E871987
|
entity |
| Predicate | primaryPassengerAirline |
P81560
|
FINISHED |
| Object | Allegiant Air |
E206746
|
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: Allegiant Air | Statement: [KBLV, primaryPassengerAirline, Allegiant Air]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPassengerAirline Context triple: [KBLV, primaryPassengerAirline, Allegiant Air]
-
A.
primaryPassengerOperatorOnRoute
Indicates that an operator is the main provider of passenger services on a specific route.
-
B.
primaryAirlinePartner
Indicates that one airline serves as the main or preferred partner airline for another entity, such as a traveler, company, or loyalty program.
-
C.
primaryHubAirline
chosen
Indicates that an airline serves as the main or principal hub carrier for a particular airport or location.
-
D.
associatedAirlinePrimaryMarket
Indicates that an airline is primarily associated with, or operates chiefly within, a particular geographic or commercial market.
-
E.
primaryAircraftOperator
Indicates that one entity is the main organization or individual responsible for operating a particular aircraft.
- F. None of above.
Provenance (4 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3692eb3d648190a0666d92fdd68619 |
completed | June 20, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:50 a.m.