Triple
T25433430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pólya’s theorem on random walks |
E637316
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | result in random walk theory |
C8028
|
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: result in random walk theory Context triple: [Pólya’s theorem on random walks, instanceOf, result in random walk theory]
-
A.
result in probability theory
chosen
In probability theory, a result is a formally stated and proven fact—such as a theorem, lemma, or corollary—that describes a property or relationship involving probabilistic concepts like random variables, events, or distributions.
-
B.
random process
A random process is a collection of random variables indexed by time or space that models the evolution of a system subject to inherent uncertainty.
-
C.
stochastic process
A stochastic process is a collection of random variables indexed by time or space that describes the evolution of a system subject to inherent randomness.
-
D.
object in optimal stopping theory
An object in optimal stopping theory is an abstract entity (such as a stochastic process, payoff function, or stopping rule) whose evolution or evaluation over time determines when it is best to stop observing and take an action to maximize expected reward or minimize expected cost.
-
E.
random variable functional
A random variable functional is a mapping that takes one or more random variables (or their distributions) as input and returns a real-valued quantity summarizing some aspect of their probabilistic behavior.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 21, 2026, 1:59 p.m.