Triple

T17676504
Position Surface form Disambiguated ID Type / Status
Subject SymTridiagonal E440654 entity
Predicate isSubtypeOf P1244 FINISHED
Object AbstractMatrix 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: AbstractMatrix | Statement: [SymTridiagonal, isSubtypeOf, AbstractMatrix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AbstractMatrix
Context triple: [SymTridiagonal, isSubtypeOf, AbstractMatrix]
  • A. AbstractMatrix chosen
    AbstractMatrix is a core Julia type that defines the generic interface and behavior for all two-dimensional array and matrix-like structures in the LinearAlgebra ecosystem.
  • B. BlockBandedMatrix
    BlockBandedMatrix is a Julia matrix type representing sparse matrices composed of dense blocks arranged in a banded structure, optimized for efficient storage and linear algebra operations.
  • C. DMatrix
    DMatrix is XGBoost’s optimized internal data structure for storing and accessing training data efficiently during model training and prediction.
  • D. MPSMatrix
    MPSMatrix is a Metal Performance Shaders class that represents and accelerates high-performance matrix computations on Apple GPUs.
  • E. Modular Transverse Matrix
    Modular Transverse Matrix is Volkswagen Group’s flexible vehicle architecture designed for front-engined, front-wheel-drive and all-wheel-drive cars, enabling shared components and production efficiencies across multiple models and brands.
  • 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.