Triple
T32187755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daily Cash |
E822151
|
entity |
| Predicate | cashBackCategory |
P63502
|
FINISHED |
| Object | Apple purchases |
—
|
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: Apple purchases | Statement: [Daily Cash, cashBackCategory, Apple purchases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cashBackCategory Context triple: [Daily Cash, cashBackCategory, Apple purchases]
-
A.
includesCreditCategory
Indicates that one entity contains or encompasses a specific credit-related category within its defined set or structure.
-
B.
canBeRebatedTo
Indicates that a cost, fee, or amount is eligible to be refunded or credited back to a specified party.
-
C.
reimbursementCategory
chosen
Indicates the classification or type under which a reimbursement claim or expense is categorized.
-
D.
payCategory
Indicates the classification of a payment or compensation into a specific category (such as type, purpose, or pay band) within a payment or payroll context.
-
E.
couponType
Indicates the specific category or kind of coupon associated with an offer or transaction.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6babc938c8190a233c3a8b5254802 |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.