Triple
T35844151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordy Club loyalty program |
E1036162
|
entity |
| Predicate | higherEarningRateFor |
P30187
|
FINISHED |
| Object | Nordstrom credit cardholders |
—
|
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: Nordstrom credit cardholders | Statement: [Nordy Club loyalty program, higherEarningRateFor, Nordstrom credit cardholders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherEarningRateFor Context triple: [Nordy Club loyalty program, higherEarningRateFor, Nordstrom credit cardholders]
-
A.
increasedRateOn
Indicates that one entity has raised the rate, fee, or charge applied to another entity.
-
B.
hasHigherOrderRate
Indicates that one entity’s rate (such as frequency, speed, or occurrence) is greater than that of another entity.
-
C.
earnsMorePointsThan
chosen
Indicates that one entity receives a greater number of points than another entity in a given context or comparison.
-
D.
payGradeComparison
Indicates that the relative pay grade or salary level between two entities is being compared (e.g., one is higher, lower, or equal to the other).
-
E.
compensationRate
Indicates the rate or amount of payment provided in exchange for a specified unit of work, time, or service.
- 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_69f76e1a29e8819088280f26096aeb55 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: May 3, 2026, 4:06 p.m.