Triple
T26992364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cilk work-stealing scheduler |
E679890
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | load-balancing algorithm |
C52349
|
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: load-balancing algorithm Context triple: [Cilk work-stealing scheduler, instanceOf, load-balancing algorithm]
-
A.
software load balancer
A software load balancer is a programmatic system that distributes incoming network or application traffic across multiple servers or services to optimize performance, reliability, and scalability.
-
B.
active queue management algorithm
An active queue management algorithm is a network mechanism that proactively controls packet queues by selectively dropping or marking packets before buffers overflow to reduce congestion, latency, and packet loss.
-
C.
distributed consensus algorithm
A distributed consensus algorithm is a protocol that enables a group of independent, networked nodes to reliably agree on a single shared value or state, even in the presence of failures or unreliable communication.
-
D.
network protocol algorithm
A network protocol algorithm is a defined set of rules and procedures that govern how data is formatted, transmitted, routed, and received across interconnected devices in a communication network.
-
E.
array partitioning algorithm
An array partitioning algorithm is a procedure that reorganizes the elements of an array into segments based on a specified criterion (such as pivot value, parity, or range) while typically preserving or controlling the relative order within or between partitions.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 27, 2026, 6:52 a.m.