Triple
T18730268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States retail industry |
E458013
|
entity |
| Predicate | paymentTrend |
P69285
|
FINISHED |
| Object | contactless payments |
—
|
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: contactless payments | Statement: [United States retail industry, paymentTrend, contactless payments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paymentTrend Context triple: [United States retail industry, paymentTrend, contactless payments]
-
A.
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.
-
B.
transactionNature
Indicates the type or character of a transaction, specifying what kind of exchange or operation is taking place between the involved parties.
-
C.
paymentChangePattern
chosen
Indicates a characteristic way in which payment amounts, timing, or methods vary or evolve over a period or across transactions.
-
D.
paymentServices
Indicates that one entity provides or facilitates payment-related services or processing for another entity.
-
E.
payType
Indicates the method or category of payment used in a transaction or compensation arrangement.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d778cf8819083500600b9ac0744 |
completed | April 20, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.