Triple
T30869835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Regional Airlines |
E786305
|
entity |
| Predicate | aircraftLeasingSource |
P173758
|
FINISHED |
| Object | Air Canada (for some Embraer 175 aircraft) |
—
|
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: Air Canada (for some Embraer 175 aircraft) | Statement: [Sky Regional Airlines, aircraftLeasingSource, Air Canada (for some Embraer 175 aircraft)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftLeasingSource Context triple: [Sky Regional Airlines, aircraftLeasingSource, Air Canada (for some Embraer 175 aircraft)]
-
A.
aircraftInFleet
Indicates that a particular aircraft is included as a member of a specified fleet.
-
B.
majorAircraftOEMCustomer
Indicates that the subject entity is a significant or primary customer of the object entity in its role as an aircraft original equipment manufacturer (OEM).
-
C.
carrierAircraft
Indicates that an aircraft is designed, equipped, or used to operate from an aircraft carrier.
-
D.
aircraftOrder
Indicates that one aircraft is positioned or sequenced before another in an ordered arrangement (such as a lineup, list, or schedule).
-
E.
airlineFleetManufacturer
Indicates that an airline’s fleet includes aircraft produced by a specific manufacturer.
- F. None of above. chosen
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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6ba1733408190af579d93a7946508 |
completed | May 3, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: April 29, 2026, 8:47 p.m.