Triple
T15502577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khinchin–Pollaczek formula |
E378997
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | result in queueing 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 queueing theory Context triple: [Khinchin–Pollaczek formula, instanceOf, result in queueing 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.
result in order theory
A result in order theory is a formally proven statement or theorem about the properties, structures, or relationships of ordered sets and order-preserving mappings.
-
C.
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.
-
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.
result in real analysis
In real analysis, a result is a proven mathematical statement—such as a theorem, lemma, proposition, or corollary—that establishes a specific property or relationship about real-valued functions, sequences, sets, or structures on the real numbers.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
Created at: April 10, 2026, 3:54 a.m.