Triple
T33412210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber Platinum |
E855616
|
entity |
| Predicate | customerRelationshipGoal |
P114366
|
FINISHED |
| Object | increase rider loyalty |
—
|
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: increase rider loyalty | Statement: [Uber Platinum, customerRelationshipGoal, increase rider loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customerRelationshipGoal Context triple: [Uber Platinum, customerRelationshipGoal, increase rider loyalty]
-
A.
relationshipToCustomers
Indicates the type or nature of connection an entity has with its customers, such as role, status, or interaction pattern.
-
B.
customerValue
Indicates the degree of benefit, importance, or worth that a customer represents to a business or organization.
-
C.
customerFocus
Indicates that one entity prioritizes understanding and meeting the needs, preferences, or satisfaction of another entity (typically a customer or client).
-
D.
relationshipGoal
chosen
Indicates that one entity has a desired or intended relationship status or type involving another entity.
-
E.
loyaltyGoal
Indicates that one entity has the objective or commitment to remain faithful, supportive, or devoted to another entity or cause.
- 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_69f3496f04a08190804e56ac5098b8e4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:36 a.m.