Triple
T2553309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Starbucks Rewards |
E56675
|
entity |
| Predicate | loyaltyPointName |
P40801
|
FINISHED |
| Object | Stars |
—
|
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: Stars | Statement: [Starbucks Rewards, loyaltyPointName, Stars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyPointName Context triple: [Starbucks Rewards, loyaltyPointName, Stars]
-
A.
loyaltyProgramName
Indicates that an entity is associated with or identified by the name of a specific loyalty or rewards program.
-
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.
laterLoyalty
Indicates that one entity becomes loyal to another at a later time, rather than from the outset of their 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. 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0c8b6f08190a68645db3e8b779a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd5a1cd508190a660b9a3c6b7cbcb |
completed | March 7, 2026, 7:37 a.m. |
Created at: March 6, 2026, 9:48 p.m.