Triple
T24953622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regional Express Holdings |
E624406
|
entity |
| Predicate | hasAirlineBrand |
P41158
|
FINISHED |
| Object | Rex Airlines |
—
|
NE NERFINISHED |
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: Rex Airlines | Statement: [Regional Express Holdings, hasAirlineBrand, Rex Airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirlineBrand Context triple: [Regional Express Holdings, hasAirlineBrand, Rex Airlines]
-
A.
airlineBrand
chosen
Indicates that one entity functions as the commercial airline brand associated with, or operating under, another entity.
-
B.
airlineAssociatedBrand
Indicates that a brand is commercially or operationally associated with a particular airline, such as through co-branding, partnership, or subsidiary relationships.
-
C.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
D.
ownsAirline
Indicates that one entity has legal ownership or controlling interest in an airline company.
-
E.
designatedAirlineType
Indicates that an airline has been assigned a specific operational or classification type for a given context or service.
- F. None of above.
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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f4490283c481908c18246dc7125eec |
completed | May 1, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:57 a.m.