Triple
T10249439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diners Club International |
E240300
|
entity |
| Predicate | hasCardProgram |
P13356
|
FINISHED |
| Object | corporate card program |
—
|
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: corporate card program | Statement: [Diners Club International, hasCardProgram, corporate card program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCardProgram Context triple: [Diners Club International, hasCardProgram, corporate card program]
-
A.
hasAwardProgram
Indicates that an entity maintains or offers a formal award or recognition program.
-
B.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
-
C.
hasMembershipProgram
chosen
Indicates that an entity offers or participates in a structured membership program, typically providing special access, benefits, or services to enrolled members.
-
D.
hasCardNumber
Indicates that an entity is associated with, or assigned, a specific card number.
-
E.
supportsLoyaltyCards
Indicates that an entity provides functionality to accept, manage, or work with loyalty cards for rewards or benefits.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:28 a.m.