Triple
T34674841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BlazingSQL |
E890466
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | RAPIDS ecosystem component |
C59861
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: RAPIDS ecosystem component Context triple: [BlazingSQL, instanceOf, RAPIDS ecosystem component]
-
A.
PyTorch ecosystem project
A PyTorch ecosystem project is a library, tool, or framework that extends or integrates with PyTorch to support tasks such as model development, training, deployment, or domain-specific applications.
-
B.
GPU memory management library
A GPU memory management library provides abstractions and utilities to efficiently allocate, deallocate, track, and optimize memory usage on graphics processing units for high-performance computing and graphics applications.
-
C.
CUDA library
A CUDA library is a collection of pre-optimized GPU-accelerated functions and tools that simplify and speed up parallel computing tasks on NVIDIA GPUs.
-
D.
GPU communication library
A GPU communication library is a software component that provides efficient, high-throughput data transfer and synchronization primitives between GPUs, often across nodes, to enable scalable parallel computation.
-
E.
GPU computing framework
A GPU computing framework is a software platform that enables developers to write, manage, and optimize parallel programs that execute on graphics processing units for high-performance computation.
- F. None of above. chosen
Provenance (1 batch)
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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 2:05 a.m.