Triple
T32308586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bessel inequality |
E825431
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | inequality in inner product spaces |
C57913
|
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: inequality in inner product spaces Context triple: [Bessel inequality, instanceOf, inequality in inner product spaces]
-
A.
norm inequality
A norm inequality is a mathematical statement that compares the sizes (norms) of vectors or functions, often establishing bounds or relationships between different norms in a vector space.
-
B.
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.
-
C.
inequality in statistics
Inequality in statistics refers to the unequal distribution of a variable (such as income, wealth, or resources) across individuals or groups, often quantified using measures like the Gini coefficient or Lorenz curve.
-
D.
inequality in information theory
An inequality in information theory is a mathematical relation that bounds or compares information-theoretic quantities—such as entropy, mutual information, or divergence—to reveal fundamental limits on data compression, communication, and inference.
-
E.
equation in functional analysis
An equation in functional analysis is a relation, typically involving functions and operators on infinite-dimensional spaces, that specifies conditions these objects must satisfy, often to study existence, uniqueness, and properties of solutions.
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:45 a.m.