Triple
T32473769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZKFailoverController |
E829912
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | high-availability controller |
C15503
|
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: high-availability controller Context triple: [ZKFailoverController, instanceOf, high-availability controller]
-
A.
high-availability operating system
A high-availability operating system is a fault-tolerant OS designed with redundancy, rapid failover, and continuous operation mechanisms to minimize downtime and ensure critical services remain accessible.
-
B.
high-availability solution
chosen
A high-availability solution is an architecture and set of mechanisms designed to ensure that a system or service remains continuously operational and accessible with minimal downtime, even in the face of failures or maintenance activities.
-
C.
high availability solution
A high availability solution is a system design and set of mechanisms that ensure critical services remain continuously accessible with minimal downtime, even in the face of failures or maintenance activities.
-
D.
Kubernetes control plane component
A Kubernetes control plane component is a core service (such as the API server, scheduler, or controller manager) that collectively manages cluster state, scheduling, and orchestration of workloads.
-
E.
control plane component
A control plane component is a system element responsible for managing, configuring, and orchestrating the behavior and state of underlying data plane resources within a distributed or networked environment.
- 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:57 a.m.