Triple
T10870760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viva Fan |
E256643
|
entity |
| Predicate | customerIncentive |
P57184
|
FINISHED |
| Object | fare discounts |
—
|
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: fare discounts | Statement: [Viva Fan, customerIncentive, fare discounts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: customerIncentive Context triple: [Viva Fan, customerIncentive, fare discounts]
-
A.
loyaltyIncentive
chosen
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
B.
campaignCredit
Indicates that credit or attribution for a campaign’s outcome, performance, or impact is assigned to a particular entity.
-
C.
couponType
Indicates the specific category or kind of coupon associated with an offer or transaction.
-
D.
loyaltyIntegration
Indicates the degree to which a loyalty or rewards program is connected, synchronized, or functionally embedded with another system, platform, or service.
-
E.
loyaltyMechanism
Indicates a mechanism or process through which loyalty is established, maintained, or reinforced between entities.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7518610e48190bee50db71ae0ca3e |
completed | April 9, 2026, 7:13 a.m. |
| PD | Predicate disambiguation | batch_69d70d360c388190a3d829fe8862434f |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.