Triple
T27513273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alaska Airlines Mileage Plan |
E694476
|
entity |
| Predicate | mileEarning |
P32734
|
FINISHED |
| Object | Alaska Airlines marketed 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: Alaska Airlines marketed flights | Statement: [Alaska Airlines Mileage Plan, mileEarning, Alaska Airlines marketed flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mileEarning Context triple: [Alaska Airlines Mileage Plan, mileEarning, Alaska Airlines marketed flights]
-
A.
mileEarningUnit
Indicates the unit or basis (e.g., per mile, per dollar) used to calculate or award mileage or points in a mileage-earning relationship.
-
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.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
D.
milesCanBePurchased
Indicates that a certain number of miles are eligible to be bought, typically in exchange for money or points.
-
E.
salaryMilestone
Indicates a specific salary-related threshold or achievement that has been reached or is being targeted in relation to an 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_69ef53842afc8190ba6bd4e4999bda67 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62efb19d08190990f13125d6cb7d5 |
completed | May 2, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 1:17 p.m.