Triple
T31293655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sizzling Pubs |
E798013
|
entity |
| Predicate | hasLoyaltyOrOffers |
P171734
|
FINISHED |
| Object | discounted meal deals |
—
|
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: discounted meal deals | Statement: [Sizzling Pubs, hasLoyaltyOrOffers, discounted meal deals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoyaltyOrOffers Context triple: [Sizzling Pubs, hasLoyaltyOrOffers, discounted meal deals]
-
A.
hasLoyalties
Indicates that an entity feels allegiance or commitment toward one or more other entities or causes.
-
B.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
C.
hasAwardProgram
Indicates that an entity maintains or offers a formal award or recognition program.
-
D.
loyaltyProgramAccess
Indicates that an entity is granted rights or eligibility to participate in a specific loyalty or rewards program.
-
E.
hasCustomerPrograms
chosen
Indicates that an entity offers or is associated with specific customer-focused programs, such as loyalty, rewards, or special service initiatives.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
Created at: April 29, 2026, 9:14 p.m.