Triple
T9573208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ConnectMiles |
E230978
|
entity |
| Predicate | earnMilesOn |
P32734
|
FINISHED |
| Object | Copa Airlines flights |
—
|
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: Copa Airlines flights | Statement: [ConnectMiles, earnMilesOn, Copa Airlines flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earnMilesOn Context triple: [ConnectMiles, earnMilesOn, Copa Airlines flights]
-
A.
associatedWithFrequentFlyerProgram
Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
-
B.
mileageAccrual
chosen
Indicates the accumulation or earning of mileage (such as distance-based points or credits) as a result of certain actions or usage.
-
C.
airportBenefit
Indicates that one entity gains an advantage, profit, or positive impact from the existence, operation, or services of an airport.
-
D.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
E.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998d79cc8190b94e5953915a5fa4 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:04 p.m.