Triple
T29090669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AKS primality test |
E734843
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | polynomial-time algorithm |
C6819
|
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: polynomial-time algorithm Context triple: [AKS primality test, instanceOf, polynomial-time algorithm]
-
A.
polynomial-time many-one reduction
A polynomial-time many-one reduction is a function computable in polynomial time that transforms instances of one decision problem into instances of another such that the original instance is a "yes" instance if and only if the transformed instance is a "yes" instance.
-
B.
algorithm
chosen
An algorithm is a finite, well-defined sequence of computational steps or rules designed to solve a specific problem or perform a particular task.
-
C.
probabilistic complexity class
A probabilistic complexity class is a set of decision problems that can be solved by a probabilistic Turing machine within specified resource bounds (such as time or space), with correctness guaranteed only with high probability rather than certainty.
-
D.
time complexity class
A time complexity class is a set of decision problems that can be solved by a computational model within a specified upper bound on running time as a function of input size.
-
E.
complexity class
A complexity class is a set of computational problems grouped together based on the resources (such as time or space) required by an algorithm to solve them under a given computational model.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
Created at: April 28, 2026, 11:04 a.m.