Triple
T4443244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LinearAlgebra |
E96219
|
entity |
| Predicate | usesBackend |
P4791
|
FINISHED |
| Object | BLAS |
E440649
|
NE FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: BLAS | Statement: [LinearAlgebra, usesBackend, BLAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BLAS Context triple: [LinearAlgebra, usesBackend, BLAS]
-
A.
BLAS
chosen
BLAS (Basic Linear Algebra Subprograms) is a standardized collection of low-level routines for performing common linear algebra operations such as vector and matrix multiplication, widely used as a performance-optimized foundation in scientific computing.
-
B.
LAPACK
LAPACK is a widely used software library that provides highly optimized routines for numerical linear algebra operations such as solving systems of equations, eigenvalue problems, and singular value decompositions.
-
C.
LINPACK
LINPACK is a widely used benchmark and software library for performing numerical linear algebra computations, particularly solving systems of linear equations.
-
D.
cuBLAS
cuBLAS is NVIDIA’s GPU-accelerated implementation of the BLAS linear algebra library, providing high-performance matrix and vector operations for CUDA applications.
-
E.
cuSPARSE
cuSPARSE is NVIDIA’s GPU-accelerated library providing high-performance sparse linear algebra routines for CUDA applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355aef21c819088f168a23f1933a6 |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6281264f08190942d2043495c89d5 |
completed | March 15, 2026, 3:31 a.m. |
Created at: March 12, 2026, 11:32 p.m.