Triple
T4092311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khinchin–Kahane type inequalities |
E87730
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | norm inequality |
C15244
|
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: norm inequality Context triple: [Khinchin–Kahane type inequalities, instanceOf, norm inequality]
-
A.
inner product space
An inner product space is a vector space equipped with an inner product, a function that assigns a scalar to each pair of vectors in a way that generalizes the dot product and induces notions of length and angle.
-
B.
stability concept in functional equations
A stability concept in functional equations studies how small deviations from an exact functional relationship affect the existence and form of nearby exact solutions, typically quantifying when approximate solutions imply true solutions close in some specified sense.
-
C.
approximation
An approximation is a value, representation, or solution that is close to, but not exactly equal to, a true or ideal quantity, used when exactness is unnecessary or unattainable.
-
D.
vector space
A vector space is a set of objects called vectors, equipped with operations of vector addition and scalar multiplication that satisfy specific axioms such as associativity, commutativity, distributivity, and the existence of additive identities and inverses.
-
E.
integral
An integral is a fundamental mathematical concept that represents the accumulation of quantities, often interpreted as the area under a curve or the total of continuously varying values.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
Created at: March 9, 2026, 3:40 p.m.