Triple

T4443242
Position Surface form Disambiguated ID Type / Status
Subject LinearAlgebra E96219 entity
Predicate exportsConstant P56535 FINISHED
Object BLAS
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.
 E440649 NE FINISHED

How this triple was built (4 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, exportsConstant, BLAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BLAS
Context triple: [LinearAlgebra, exportsConstant, BLAS]
  • A. LINPACK
    LINPACK is a widely used benchmark and software library for performing numerical linear algebra computations, particularly solving systems of linear equations.
  • B. cuBLAS
    cuBLAS is NVIDIA’s GPU-accelerated implementation of the BLAS linear algebra library, providing high-performance matrix and vector operations for CUDA applications.
  • C. cuSPARSE
    cuSPARSE is NVIDIA’s GPU-accelerated library providing high-performance sparse linear algebra routines for CUDA applications.
  • D. LinearAlgebra
    LinearAlgebra is Julia’s standard library module providing core functionality for vectors, matrices, and advanced linear algebra operations.
  • E. XLA
    XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes and accelerates machine learning computations on hardware such as TPUs and GPUs.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BLAS
Triple: [LinearAlgebra, exportsConstant, BLAS]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BLAS
Target entity description: 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.
  • A. LINPACK
    LINPACK is a widely used benchmark and software library for performing numerical linear algebra computations, particularly solving systems of linear equations.
  • B. cuBLAS
    cuBLAS is NVIDIA’s GPU-accelerated implementation of the BLAS linear algebra library, providing high-performance matrix and vector operations for CUDA applications.
  • C. cuSPARSE
    cuSPARSE is NVIDIA’s GPU-accelerated library providing high-performance sparse linear algebra routines for CUDA applications.
  • D. LinearAlgebra
    LinearAlgebra is Julia’s standard library module providing core functionality for vectors, matrices, and advanced linear algebra operations.
  • E. XLA
    XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes and accelerates machine learning computations on hardware such as TPUs and GPUs.
  • F. None of above. chosen

Provenance (5 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_69b3564216b081908c41109100b36862 completed March 13, 2026, 12:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69b61382d00481908b7c84f337b5cad7 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b6177d1a588190991fddf506239d22 completed March 15, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69b61b6bc1448190b30d444a821bb1a5 completed March 15, 2026, 2:37 a.m.
Created at: March 12, 2026, 11:32 p.m.