Triple
T26992312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | fat-tree network topology |
E679889
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | interconnection network |
C905
|
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: interconnection network Context triple: [fat-tree network topology, instanceOf, interconnection network]
-
A.
high-performance computing interconnect
A high-performance computing interconnect is a specialized, low-latency, high-bandwidth communication network that links compute nodes in large-scale systems to enable fast data exchange and efficient parallel processing.
-
B.
high-performance computing interconnect device
A high-performance computing interconnect device is specialized hardware that links compute nodes with low-latency, high-bandwidth communication to enable efficient parallel processing in large-scale systems.
-
C.
InfiniBand interconnect generation
InfiniBand interconnect generation represents the process and configuration logic for creating, parameterizing, and managing high-speed InfiniBand fabric topologies and their associated connectivity resources.
-
D.
network architecture
chosen
A network architecture is the structured design and organization of hardware, software, protocols, and communication paths that define how data flows and services are delivered within a computer network.
-
E.
parallel computer bus
A parallel computer bus is a communication system that transfers multiple bits of data simultaneously across multiple wires or channels between components within a computer system.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 27, 2026, 6:52 a.m.