Triple

T17676496
Position Surface form Disambiguated ID Type / Status
Subject SymTridiagonal E440654 entity
Predicate providedBy P67 FINISHED
Object LinearAlgebra.jl 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: LinearAlgebra.jl | Statement: [SymTridiagonal, providedBy, LinearAlgebra.jl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LinearAlgebra.jl
Context triple: [SymTridiagonal, providedBy, LinearAlgebra.jl]
  • A. LinearAlgebra chosen
    LinearAlgebra is Julia’s standard library module providing core functionality for vectors, matrices, and advanced linear algebra operations.
  • B. linear algebra
    Linear algebra is a branch of mathematics that studies vectors, vector spaces, linear transformations, and systems of linear equations, forming a foundation for many areas of science and engineering.
  • C. LINPACK
    LINPACK is a widely used benchmark and software library for performing numerical linear algebra computations, particularly solving systems of linear equations.
  • D. 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.
  • E. arpack
    arpack is a numerical software library for efficiently computing a few eigenvalues and eigenvectors of large sparse matrices, commonly used in scientific computing and machine learning.
  • 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6d9ab88190ab0e25eac8b0101c completed April 19, 2026, 6 a.m.
Created at: April 10, 2026, 10:01 a.m.