Triple
T13320098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD Instinct |
E317291
|
entity |
| Predicate | supportsEcosystem |
P1888
|
FINISHED |
| Object | ROCm |
E956196
|
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: ROCm | Statement: [AMD Instinct, supportsEcosystem, ROCm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ROCm Context triple: [AMD Instinct, supportsEcosystem, ROCm]
-
A.
ROCm
chosen
ROCm is AMD’s open-source software platform for GPU computing, providing tools, libraries, and drivers for high-performance and heterogeneous computing workloads.
-
B.
AMD ROCm software stack
AMD ROCm software stack is AMD’s open-source GPU computing platform that provides tools, libraries, and runtimes for high-performance computing and machine learning on AMD GPUs.
-
C.
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.
-
D.
NVIDIA CUDA-X AI
NVIDIA CUDA-X AI is a GPU-accelerated software stack from NVIDIA that provides optimized libraries, tools, and frameworks for building and deploying high-performance AI and data science applications.
-
E.
NVIDIA TensorRT
NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime library designed to accelerate AI models on NVIDIA GPUs in production environments.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990faa95481908a7fd297959c062e |
completed | April 11, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716ee695c81909ffeeb0901ee66c1 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:29 p.m.