Triple
T10882144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA RAPIDS |
E256948
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object | cuSignal |
E758502
|
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: cuSignal | Statement: [NVIDIA RAPIDS, component, cuSignal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: cuSignal Context triple: [NVIDIA RAPIDS, component, cuSignal]
-
A.
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.
-
B.
CUDA Runtime API
The CUDA Runtime API is a high-level programming interface that simplifies developing and managing GPU-accelerated applications on NVIDIA GPUs.
-
C.
CUE
CUE is Kenya’s national regulatory body responsible for quality assurance, accreditation, and standards in university education.
-
D.
CUDA toolkit
CUDA Toolkit is NVIDIA’s software development platform that provides compilers, libraries, and tools for building and optimizing GPU-accelerated applications.
-
E.
CUDA libraries
chosen
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.
- 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_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. |
Created at: April 8, 2026, 9:21 p.m.