Triple
T28249633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MQMs |
E712277
|
entity |
| Predicate | loyaltyProgramTierMetric |
P127274
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [MQMs, loyaltyProgramTierMetric, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyProgramTierMetric Context triple: [MQMs, loyaltyProgramTierMetric, yes]
-
A.
loyaltyProgramTierOf
Indicates the specific loyalty or rewards program tier that an entity (such as a customer or account) belongs to.
-
B.
loyaltyProgramTierDependent
chosen
Indicates that the applicability, behavior, or outcome of something depends on a customer's current tier or level within a loyalty program.
-
C.
loyaltyDimension
Indicates the degree or aspect of loyalty characterizing the relationship between entities.
-
D.
loyaltyProgramType
Indicates the specific category or kind of loyalty program associated with an entity (such as points-based, tiered, or subscription-based).
-
E.
loyaltyArc
Indicates a character’s progression in loyalty toward another entity, typically showing how trust, allegiance, or faithfulness strengthens, weakens, or transforms over time.
- 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.