Triple
T27585561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Netezza Performance Server |
E699682
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | data warehouse appliance |
C25904
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: data warehouse appliance Context triple: [IBM Netezza Performance Server, instanceOf, data warehouse appliance]
-
A.
in-memory analytics appliance
An in-memory analytics appliance is a specialized hardware and software system that stores and processes data entirely in RAM to deliver extremely fast, interactive analytical querying and reporting.
-
B.
data warehouse platform
chosen
A data warehouse platform is an integrated system that collects, stores, and organizes large volumes of structured data from multiple sources to support efficient querying, reporting, and analytics for business decision-making.
-
C.
in-memory analytical engine
An in-memory analytical engine is a system that stores and processes data directly in main memory to enable extremely fast, interactive analytical queries and complex computations.
-
D.
online analytical processing server
An online analytical processing server is a specialized system that stores, organizes, and processes multidimensional data to support fast, complex analytical queries and business intelligence reporting.
-
E.
in-memory analytics engine
An in-memory analytics engine is a software system that stores and processes data primarily in main memory to deliver extremely fast analytical queries and real-time insights.
- F. None of above.
Provenance (1 batch)
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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
Created at: April 27, 2026, 2:04 p.m.