Triple

T15313841
Position Surface form Disambiguated ID Type / Status
Subject Caffe E366103 entity
Predicate programmingLanguage P1592 FINISHED
Object CUDA E41922 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 | Statement: [Caffe, programmingLanguage, CUDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CUDA
Context triple: [Caffe, programmingLanguage, CUDA]
  • A. NVIDIA CUDA chosen
    NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
  • 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. GPU
    The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
  • E. GPU
    A GPU (Graphics Processing Unit) is a highly parallel processor originally designed for rendering graphics that is now widely used to accelerate compute-intensive tasks such as machine learning, scientific simulations, and video processing.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd050108190a584543cb93943a4 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a3da3881909b50cfbec0543adc completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.