Triple
T8623496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U6 |
E204224
|
entity |
| Predicate | airlinePassengerOrCargo |
P881
|
FINISHED |
| Object | passenger airline |
—
|
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: passenger airline | Statement: [U6, airlinePassengerOrCargo, passenger airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlinePassengerOrCargo Context triple: [U6, airlinePassengerOrCargo, passenger airline]
-
A.
hasPassengerShipping
Indicates that one entity provides or is involved in passenger shipping services or transport for another entity.
-
B.
hasCargoAirline
Indicates that one entity operates as a cargo airline for, or provides cargo air transport services to, another entity.
-
C.
hasPassengerOperator
Indicates that an entity (such as a vehicle or service) is operated by an organization or person responsible for carrying passengers.
-
D.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
E.
passengers
chosen
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:26 p.m.