Triple

T17676455
Position Surface form Disambiguated ID Type / Status
Subject Bidiagonal matrix E440653 entity
Predicate isUsedFor P98 FINISHED
Object Singular value decomposition NE NERFINISHED

How this triple was built (3 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: Singular value decomposition | Statement: [Bidiagonal matrix, isUsedFor, Singular value decomposition]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Singular value decomposition
Context triple: [Bidiagonal matrix, isUsedFor, Singular value decomposition]
  • A. SVD
    SVD is the abbreviation for the Special Victims Division, a specialized police unit that investigates sensitive crimes such as sexual offenses and crimes against vulnerable victims.
  • B. SVD
    SVD is the IATA airport code for Argyle International Airport, the main international gateway to Saint Vincent and the Grenadines in the Caribbean.
  • C. CP decomposition
    CP decomposition (CANDECOMP/PARAFAC) is a tensor factorization method that expresses a multi-way array as a sum of rank-one components, widely used for data analysis in fields like signal processing, chemometrics, and machine learning.
  • D. Jacobi eigenvalue algorithm
    The Jacobi eigenvalue algorithm is an iterative numerical method for computing all eigenvalues and eigenvectors of a real symmetric matrix by applying a sequence of orthogonal similarity transformations.
  • E. Bartels–Stewart algorithm
    The Bartels–Stewart algorithm is a numerical linear algebra method that efficiently solves certain matrix equations, particularly Sylvester and Lyapunov equations, using Schur decompositions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Singular value decomposition
Target entity description: Singular value decomposition is a fundamental matrix factorization technique that expresses a matrix as the product of two orthogonal (or unitary) matrices and a diagonal matrix of singular values, widely used in numerical analysis, data compression, and dimensionality reduction.
  • A. SVD
    SVD is the abbreviation for the Special Victims Division, a specialized police unit that investigates sensitive crimes such as sexual offenses and crimes against vulnerable victims.
  • B. SVD
    SVD is the IATA airport code for Argyle International Airport, the main international gateway to Saint Vincent and the Grenadines in the Caribbean.
  • C. CP decomposition
    CP decomposition (CANDECOMP/PARAFAC) is a tensor factorization method that expresses a multi-way array as a sum of rank-one components, widely used for data analysis in fields like signal processing, chemometrics, and machine learning.
  • D. Jacobi eigenvalue algorithm
    The Jacobi eigenvalue algorithm is an iterative numerical method for computing all eigenvalues and eigenvectors of a real symmetric matrix by applying a sequence of orthogonal similarity transformations.
  • E. Bartels–Stewart algorithm
    The Bartels–Stewart algorithm is a numerical linear algebra method that efficiently solves certain matrix equations, particularly Sylvester and Lyapunov equations, using Schur decompositions.
  • F. None of above. chosen

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.