Triple
T21046322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thurston norm |
E518459
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | seminorm |
C44530
|
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: seminorm Context triple: [Thurston norm, instanceOf, seminorm]
-
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.
pseudometric
A pseudometric is a function that assigns a nonnegative real number as a "distance" between any two points in a set, satisfying all the axioms of a metric except that distinct points are allowed to have zero distance.
-
C.
Banach space (for suitable norms)
A Banach space is a vector space over the real or complex numbers equipped with a norm (from a suitable class of norms) such that every Cauchy sequence with respect to that norm converges to a limit within the space.
-
D.
semigroup of operators
A semigroup of operators is a family of linear operators on a space, indexed by a semigroup (often time), such that the composition of operators matches the semigroup operation and typically includes an identity at the neutral element.
-
E.
generalization of Lebesgue spaces
A generalization of Lebesgue spaces is a function space framework that extends classical \(L^p\) spaces by relaxing or modifying their integrability, norm, or measure-theoretic structure to capture more nuanced behaviors of functions and distributions.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
Created at: April 16, 2026, 2:34 p.m.