Triple

T18257172
Position Surface form Disambiguated ID Type / Status
Subject Cleve Moler E437245 entity
Predicate notableWork P4 FINISHED
Object LINPACK NE NERFINISHED

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: LINPACK | Statement: [Cleve Moler, notableWork, LINPACK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LINPACK
Context triple: [Cleve Moler, notableWork, LINPACK]
  • A. LINPACK chosen
    LINPACK is a widely used benchmark and software library for performing numerical linear algebra computations, particularly solving systems of linear equations.
  • 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. EISPACK
    EISPACK is a numerical software library written in Fortran for computing eigenvalues and eigenvectors of matrices, widely used before being superseded by LAPACK.
  • D. 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.
  • E. ScaLAPACK
    ScaLAPACK is a high-performance library for solving large-scale linear algebra problems on distributed-memory parallel computers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd86e21081909c049082949b95c6 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:34 a.m.