Triple
T14557263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FedMart |
E341571
|
entity |
| Predicate | targetedCustomerSegment |
P16877
|
FINISHED |
| Object | value-conscious consumers |
—
|
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: value-conscious consumers | Statement: [FedMart, targetedCustomerSegment, value-conscious consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetedCustomerSegment Context triple: [FedMart, targetedCustomerSegment, value-conscious consumers]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
brandSegment
chosen
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
C.
targetedPopulation
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
D.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
E.
passengerSegments
Indicates a relationship where a journey or trip is divided into distinct legs or segments that a passenger travels through.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.