Triple

T10882137
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA RAPIDS E256948 entity
Predicate component P35 FINISHED
Object cuML
cuML is a GPU-accelerated machine learning library in the NVIDIA RAPIDS ecosystem that provides scalable, high-performance implementations of common ML algorithms.
 E890458 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: cuML | Statement: [NVIDIA RAPIDS, component, cuML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: cuML
Context triple: [NVIDIA RAPIDS, component, cuML]
  • A. NVIDIA RAPIDS
    NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
  • B. cuSOLVER
    cuSOLVER is an NVIDIA GPU-accelerated linear algebra library that provides high-performance routines for solving dense and sparse systems of equations, eigenvalue problems, and related numerical tasks.
  • C. cuBLAS
    cuBLAS is NVIDIA’s GPU-accelerated implementation of the BLAS linear algebra library, providing high-performance matrix and vector operations for CUDA applications.
  • D. cuSPARSE
    cuSPARSE is NVIDIA’s GPU-accelerated library providing high-performance sparse linear algebra routines for CUDA applications.
  • E. CuPy
    CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
  • 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: cuML
Triple: [NVIDIA RAPIDS, component, cuML]
Generated description
cuML is a GPU-accelerated machine learning library in the NVIDIA RAPIDS ecosystem that provides scalable, high-performance implementations of common ML algorithms.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: cuML
Target entity description: cuML is a GPU-accelerated machine learning library in the NVIDIA RAPIDS ecosystem that provides scalable, high-performance implementations of common ML algorithms.
  • A. NVIDIA RAPIDS
    NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
  • B. cuSOLVER
    cuSOLVER is an NVIDIA GPU-accelerated linear algebra library that provides high-performance routines for solving dense and sparse systems of equations, eigenvalue problems, and related numerical tasks.
  • C. cuBLAS
    cuBLAS is NVIDIA’s GPU-accelerated implementation of the BLAS linear algebra library, providing high-performance matrix and vector operations for CUDA applications.
  • D. cuSPARSE
    cuSPARSE is NVIDIA’s GPU-accelerated library providing high-performance sparse linear algebra routines for CUDA applications.
  • E. CuPy
    CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751da559c819094c3680a9f734ee7 completed April 9, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7e479cc81909fb8510364d6fc0e completed April 15, 2026, 8:41 p.m.
NEDg Description generation batch_69e002709d38819099c4402d30824612 completed April 15, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_69e005873ba48190b8c24c77611562fa completed April 15, 2026, 9:39 p.m.
Created at: April 8, 2026, 9:21 p.m.