Triple
T26318469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FlashArray |
E662036
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | all-flash storage array platform |
C26553
|
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: all-flash storage array platform Context triple: [FlashArray, instanceOf, all-flash storage array platform]
-
A.
all-flash storage array
chosen
An all-flash storage array is a high-performance data storage system that uses only solid-state drives (SSDs) to deliver low-latency, high-throughput access to data for enterprise applications.
-
B.
flash storage array family
A flash storage array family is a group of related all-flash storage systems that share a common architecture, features, and management model to deliver high-performance, low-latency data storage for diverse workloads.
-
C.
software-defined storage platform
A software-defined storage platform is an abstracted, policy-driven storage system that virtualizes underlying hardware resources to deliver flexible, scalable, and centrally managed data services.
-
D.
data center platform
A data center platform is an integrated environment of hardware, software, and management tools that provides scalable, secure, and reliable infrastructure for hosting, processing, and managing data and applications.
-
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.
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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
Created at: April 26, 2026, 10:26 p.m.