Triple
T17676402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SparseMatrixCSC |
E440652
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | sparse matrix type |
C39522
|
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: sparse matrix type Context triple: [SparseMatrixCSC, instanceOf, sparse matrix type]
-
A.
structured matrix
A structured matrix is a matrix whose entries follow a specific pattern or rule (such as Toeplitz, circulant, or banded structure), enabling more efficient storage and computation than a general dense matrix.
-
B.
tensor
A tensor is a multidimensional array of numerical values that generalizes scalars, vectors, and matrices to represent data or linear relationships across multiple dimensions.
-
C.
numerical linear algebra library
A numerical linear algebra library is a collection of optimized routines and data structures for performing matrix and vector operations, decompositions, and related numerical computations.
-
D.
matrix basis set
A matrix basis set is a collection of matrices that forms a minimal, linearly independent set spanning a matrix space, allowing any matrix in that space to be expressed as a unique linear combination of those basis matrices.
-
E.
GPU-accelerated BLAS library
A GPU-accelerated BLAS library is a collection of highly optimized linear algebra routines that offload matrix and vector computations to graphics processing units to achieve significantly higher performance than CPU-only implementations.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
Created at: April 10, 2026, 10:01 a.m.