Triple
T4518780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeroflot Bonus |
E103214
|
entity |
| Predicate | loyaltyIncentive |
P57184
|
FINISHED |
| Object | tier status |
—
|
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: tier status | Statement: [Aeroflot Bonus, loyaltyIncentive, tier status]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyIncentive Context triple: [Aeroflot Bonus, loyaltyIncentive, tier status]
-
A.
loyaltyIntegration
Indicates the degree to which a loyalty or rewards program is connected, synchronized, or functionally embedded with another system, platform, or service.
-
B.
loyaltyProgramType
Indicates the specific category or kind of loyalty program associated with an entity (such as points-based, tiered, or subscription-based).
-
C.
loyaltyDomain
Indicates a relationship where loyalty, allegiance, or steadfast support is directed toward or governed by a particular domain, context, or sphere of influence.
-
D.
loyaltyProgramName
Indicates that an entity is associated with or identified by the name of a specific loyalty or rewards program.
-
E.
laterLoyalty
Indicates that one entity becomes loyal to another at a later time, rather than from the outset of their relationship.
- F. None of above. chosen
Provenance (4 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd57465a10819086866e29f7a6eb02 |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521abea48190b3e758a1f98dd55e |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:02 p.m.