Triple
T27637306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAP HANA |
E696503
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | in-memory database |
C53066
|
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: in-memory database Context triple: [SAP HANA, instanceOf, in-memory database]
-
A.
in-memory storage engine
An in-memory storage engine is a data management component that stores and processes all data directly in main memory rather than on disk to achieve extremely low-latency access and high throughput.
-
B.
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.
-
C.
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.
-
D.
managed in-memory data store service
A managed in-memory data store service is a cloud-based solution that provides fast, scalable, and fully administered in-memory caching and data storage capabilities without requiring users to manage underlying infrastructure.
-
E.
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.
- F. None of above. chosen
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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 27, 2026, 2:24 p.m.