Triple
T6107661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diet Pepsi |
E136154
|
entity |
| Predicate | hasTargetConsumerSegment |
P55993
|
FINISHED |
| Object | calorie-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: calorie-conscious consumers | Statement: [Diet Pepsi, hasTargetConsumerSegment, calorie-conscious consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetConsumerSegment Context triple: [Diet Pepsi, hasTargetConsumerSegment, calorie-conscious consumers]
-
A.
hasMarketingTarget
chosen
Indicates that an entity is aimed at or intended to appeal to a specific marketing audience or segment.
-
B.
usesTargetingSystem
Indicates that an entity employs or relies on a specific targeting system to aim at or select a target.
-
C.
hasTargetAudienceRegion
Indicates that something is intended for or directed toward an audience located in a specific geographic region.
-
D.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
E.
hasExpressSegments
Indicates that a route, service, or path includes segments that are designated as express, skipping certain intermediate stops or steps.
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b81fad081909b622cafc6d51249 |
completed | March 22, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c049f80e2081909b7d84a104cda68d |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.