Triple
T38211997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radisson Blu |
E1010572
|
entity |
| Predicate | partOfLoyaltyProgram |
P86203
|
FINISHED |
| Object | Radisson Rewards |
E1320687
|
NE 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: Radisson Rewards | Statement: [Radisson Blu, partOfLoyaltyProgram, Radisson Rewards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfLoyaltyProgram Context triple: [Radisson Blu, partOfLoyaltyProgram, Radisson Rewards]
-
A.
loyaltyProgramType
Indicates the specific category or kind of loyalty program associated with an entity (such as points-based, tiered, or subscription-based).
-
B.
loyaltyProgramPartner
Indicates that there is a partnership or affiliation between entities within the same loyalty or rewards program.
-
C.
loyaltyProgramAccess
chosen
Indicates that an entity is granted rights or eligibility to participate in a specific loyalty or rewards program.
-
D.
loyaltyProgramLinkedTo
Indicates that a loyalty program is associated or connected to a particular entity, such that benefits, points, or rewards can be tracked or applied through that relationship.
-
E.
hasLoyalties
Indicates that an entity feels allegiance or commitment toward one or more other entities or causes.
- F. None of above.
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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a01b130f6808190b86442fb16930e6e |
completed | May 11, 2026, 10:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a418548be9081909e1f737983642fb4 |
completed | June 28, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_6a01b023157881909a802e06eced3e2f |
completed | May 11, 2026, 10:32 a.m. |
Created at: May 3, 2026, 4:30 p.m.