Triple
T25437579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mesa Air Group |
E637416
|
entity |
| Predicate | fleetTypeOperatedThroughSubsidiary |
P62605
|
FINISHED |
| Object | regional jets |
—
|
LITERAL 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: regional jets | Statement: [Mesa Air Group, fleetTypeOperatedThroughSubsidiary, regional jets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fleetTypeOperatedThroughSubsidiary Context triple: [Mesa Air Group, fleetTypeOperatedThroughSubsidiary, regional jets]
-
A.
fleetTypeOperated
chosen
Indicates that an entity operates or manages a particular type or category of fleet.
-
B.
fleetType
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
C.
freightSubsidiary
Indicates that one entity is a subsidiary company specifically involved in freight or cargo operations for another entity.
-
D.
fleetName
Indicates the name assigned to a particular fleet within a system or context.
-
E.
airlineOwnershipType
Indicates the type or nature of ownership relationship that exists between an airline and its owning entity.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6e36f3c819084cb3f9d2ecec135 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 2 p.m.