Triple
T3694330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrich Wilhelm von Lossberg |
E78418
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Hessian general |
C14127
|
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: Hessian general Context triple: [Friedrich Wilhelm von Lossberg, instanceOf, Hessian general]
-
A.
symmetric tensor
A symmetric tensor is a multilinear map or multidimensional array whose components remain unchanged under any permutation of its indices.
-
B.
Green’s function in Euclidean space
A Green’s function in Euclidean space is a fundamental solution to a linear differential operator that represents the response at one point due to a unit source located at another point, enabling the construction of solutions to boundary value problems via superposition.
-
C.
equation in the calculus of variations
An equation in the calculus of variations is a mathematical relation, typically an Euler–Lagrange equation, that characterizes the functions making a given functional stationary (usually minimizing or maximizing its value).
-
D.
(0,2)-tensor
A (0,2)-tensor is a bilinear map that takes two vectors as input and returns a scalar, often representing objects like metrics or covariant tensor fields on a vector space or manifold.
-
E.
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.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
Created at: March 8, 2026, 3:26 p.m.