Triple
T28249768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delta Air Lines loyalty program |
E712280
|
entity |
| Predicate | eliteStatusBenefitIncludes |
P2188
|
FINISHED |
| Object | bonus miles earning |
—
|
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: bonus miles earning | Statement: [Delta Air Lines loyalty program, eliteStatusBenefitIncludes, bonus miles earning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eliteStatusBenefitIncludes Context triple: [Delta Air Lines loyalty program, eliteStatusBenefitIncludes, bonus miles earning]
-
A.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
B.
eliteStatusProgram
Indicates a relationship where an entity is enrolled in or associated with a special high-tier or privileged status program.
-
C.
isTopTierBenefit
Indicates that a benefit belongs to the highest or most premium level within a defined benefit hierarchy or structure.
-
D.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
E.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f643ee1a1881909a7f4588daba8eca |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:03 p.m.