Triple

T10068663
Position Surface form Disambiguated ID Type / Status
Subject cuSPARSE E213160 entity
Predicate requires P100 FINISHED
Object CUDA runtime E764026 NE FINISHED

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: CUDA runtime | Statement: [cuSPARSE, requires, CUDA runtime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CUDA runtime
Context triple: [cuSPARSE, requires, CUDA runtime]
  • A. CUDA Runtime API chosen
    The CUDA Runtime API is a high-level programming interface that simplifies developing and managing GPU-accelerated applications on NVIDIA GPUs.
  • B. CUDA libraries
    CUDA libraries are a collection of NVIDIA-provided GPU-accelerated software libraries that offer optimized routines for tasks such as linear algebra, deep learning, signal processing, and parallel algorithms on CUDA-enabled hardware.
  • C. CUDA toolkit
    CUDA Toolkit is NVIDIA’s software development platform that provides compilers, libraries, and tools for building and optimizing GPU-accelerated applications.
  • D. CUDA Driver API
    The CUDA Driver API is a low-level programming interface from NVIDIA that gives developers fine-grained control over GPU resources and execution for CUDA applications.
  • E. NVIDIA CUDA
    NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcff8d9c08190bc030f1dcc696310 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cbb441388190bf01925b8624377d completed April 5, 2026, 8:53 p.m.
Created at: March 30, 2026, 8:58 p.m.