Triple
T15030875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | stress–energy tensor |
E378339
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | energy–momentum 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: energy–momentum tensor Context triple: [stress–energy tensor, instanceOf, energy–momentum tensor]
-
A.
tensor calculus
Tensor calculus is a branch of mathematics that generalizes vector calculus to tensors, providing coordinate-independent tools for analyzing multidimensional quantities and their transformations, especially in physics and differential geometry.
-
B.
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.
-
C.
tensor field
A tensor field is a mathematical object that assigns a tensor (a multilinear map or multidimensional array following specific transformation rules) to every point in a space or manifold, varying smoothly from point to point.
-
D.
symmetric tensor
A symmetric tensor is a multilinear map or multidimensional array whose components remain unchanged under any permutation of its indices.
-
E.
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.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
Created at: April 10, 2026, 2:59 a.m.