Triple
T9800716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Discover Bank |
E237828
|
entity |
| Predicate | offersRewardProgram |
P57184
|
FINISHED |
| Object | cashback rewards on credit cards |
—
|
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: cashback rewards on credit cards | Statement: [Discover Bank, offersRewardProgram, cashback rewards on credit cards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersRewardProgram Context triple: [Discover Bank, offersRewardProgram, cashback rewards on credit cards]
-
A.
offersRewardFor
Indicates that one entity promises or provides a reward in exchange for another entity performing a specified action or achieving a particular outcome.
-
B.
loyaltyIncentive
chosen
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
C.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
D.
hasAwardProgram
Indicates that an entity maintains or offers a formal award or recognition program.
-
E.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62a11a88190880e0cce24923b14 |
completed | April 1, 2026, 11:11 p.m. |
| PD | Predicate disambiguation | batch_69cd03da45a88190b71b1be3354c15a6 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.