Triple
T32308549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | first Piola–Kirchhoff stress tensor |
E825430
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Piola–Kirchhoff stress tensor |
C2815
|
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: Piola–Kirchhoff stress tensor Context triple: [first Piola–Kirchhoff stress tensor, instanceOf, Piola–Kirchhoff stress tensor]
-
A.
nonlinear elasticity model
A nonlinear elasticity model describes how materials deform under loads when the relationship between stress and strain is nonlinear, capturing large deformations and material behaviors beyond the assumptions of linear elasticity.
-
B.
elastic modulus
Elastic modulus is a material property that quantifies the ratio of stress to strain within the elastic (reversible deformation) region, indicating the material’s stiffness.
-
C.
rank-2 tensor
chosen
A rank-2 tensor is a mathematical object that can be represented as a matrix whose components transform with two indices under a change of basis, generalizing linear maps and bilinear forms in vector spaces.
-
D.
curvature tensor
A curvature tensor is a multilinear mathematical object in differential geometry that measures how much a space (or manifold) deviates from being flat by quantifying the failure of vectors to return to their original direction after parallel transport around infinitesimal loops.
-
E.
symmetric tensor
A symmetric tensor is a multilinear map or multidimensional array whose components remain unchanged under any permutation of its indices.
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:45 a.m.