Triple
T5229438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirac matrices |
E118071
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | representation of Clifford algebra |
C17864
|
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: representation of Clifford algebra Context triple: [Dirac matrices, instanceOf, representation of Clifford algebra]
-
A.
Lie algebra generators
Lie algebra generators are the fundamental elements of a Lie algebra whose linear combinations and commutators encode the infinitesimal symmetries and structure constants of a continuous symmetry group.
-
B.
(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.
-
C.
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.
-
D.
SU(3) generators
SU(3) generators are the eight linearly independent, traceless, Hermitian 3×3 matrices (often represented by the Gell-Mann matrices) that form a basis for the Lie algebra su(3), defining the infinitesimal symmetries of the SU(3) group.
-
E.
rank-2 tensor
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. 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
Created at: March 20, 2026, 1:48 p.m.