Triple
T321798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro |
E6428
|
entity |
| Predicate | hasTargetMarket |
P481
|
FINISHED |
| Object | high-end consumer |
—
|
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: high-end consumer | Statement: [MacBook Pro, hasTargetMarket, high-end consumer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetMarket Context triple: [MacBook Pro, hasTargetMarket, high-end consumer]
-
A.
targetMarket
chosen
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
C.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
D.
marketedFor
Indicates that something is promoted, advertised, or positioned as being intended or suitable for a particular use, audience, or purpose.
-
E.
hasMarketParticipants
Indicates that a market or trading venue involves or is associated with specific participating entities (such as buyers, sellers, or intermediaries).
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea81a1e88190b3496070eb3d85f5 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e948048c819098ba4de9261ef2ef |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.