Triple
T33366850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HPE StoreOnce |
E854379
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | data protection appliance family |
C58252
|
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 protection appliance family Context triple: [HPE StoreOnce, instanceOf, data protection appliance family]
-
A.
data protection solution
A data protection solution is a system or set of tools and practices designed to safeguard data from loss, corruption, unauthorized access, and misuse throughout its lifecycle.
-
B.
data center security product
A data center security product is a solution that protects physical and virtual data center assets by monitoring, controlling, and securing access, network traffic, and system activities against unauthorized use, breaches, and disruptions.
-
C.
deduplication appliance
chosen
A deduplication appliance is a specialized hardware or virtual device that identifies and eliminates redundant data across storage systems to reduce capacity usage and improve backup and recovery efficiency.
-
D.
network appliance
A network appliance is a dedicated hardware or virtual device designed to perform specific network-related functions—such as routing, firewalling, load balancing, or traffic monitoring—to optimize, secure, and manage data communications within a network.
-
E.
cloud-native application protection platform
A cloud-native application protection platform is an integrated security solution that safeguards cloud-native applications across the entire lifecycle—covering development, deployment, and runtime—by unifying vulnerability management, configuration security, runtime threat detection, and compliance for containers, Kubernetes, serverless, and related cloud services.
- 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_69f3496bda8c8190bfc8fade9d1b791c |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:35 a.m.