Triple
T6894353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GarudaMiles |
E159132
|
entity |
| Predicate | tierBenefitType |
P7916
|
FINISHED |
| Object | bonus miles |
—
|
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 | Statement: [GarudaMiles, tierBenefitType, bonus miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tierBenefitType Context triple: [GarudaMiles, tierBenefitType, bonus miles]
-
A.
typeOfIncentive
chosen
Indicates the specific kind or category of incentive associated with an entity or action.
-
B.
benefitStructure
Indicates a relationship where one entity defines, organizes, or governs the benefits (such as advantages, compensations, or perks) provided to or associated with another entity.
-
C.
exclusiveBenefit
Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
-
D.
commissionType
Indicates the specific kind or category of commission arrangement that applies to a given transaction or relationship.
-
E.
loyaltyProgramTierOf
Indicates the specific loyalty or rewards program tier that an entity (such as a customer or account) belongs to.
- 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_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d931da24819096b9b205f2c0ebb0 |
completed | March 27, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:24 p.m.