Triple
T13320121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD Instinct |
E317291
|
entity |
| Predicate | brandingOf |
P1500
|
FINISHED |
| Object |
AMD data center GPU accelerators
AMD data center GPU accelerators are high-performance graphics processors designed to accelerate compute-intensive workloads such as AI, machine learning, and high-performance computing in server and cloud environments.
|
E1033642
|
NE FINISHED |
How this triple was built (4 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: AMD data center GPU accelerators | Statement: [AMD Instinct, brandingOf, AMD data center GPU accelerators]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AMD data center GPU accelerators Context triple: [AMD Instinct, brandingOf, AMD data center GPU accelerators]
-
A.
NVIDIA Tesla data center GPUs
NVIDIA Tesla data center GPUs are high-performance graphics processing units designed for accelerated computing workloads such as AI, machine learning, and high-performance computing in server and data center environments.
-
B.
AMD Radeon GCN-based GPU
The AMD Radeon GCN-based GPU is a graphics processor architecture from AMD’s Graphics Core Next family, widely used in gaming consoles and PCs for efficient, parallel graphics and compute performance.
-
C.
AMD TeraScale architecture
AMD TeraScale architecture is a previous-generation GPU microarchitecture from AMD used in earlier Radeon graphics cards, known for introducing a unified shader design before being succeeded by the GCN architecture.
-
D.
AMD Radeon GPUs
AMD Radeon GPUs are a family of graphics processing units from AMD designed for gaming, professional visualization, and compute workloads, competing directly with NVIDIA’s GeForce and other discrete graphics solutions.
-
E.
AMD Radeon RX Vega series
The AMD Radeon RX Vega series is a family of high-end graphics cards based on AMD’s Vega architecture, designed for demanding gaming and professional graphics workloads.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AMD data center GPU accelerators Triple: [AMD Instinct, brandingOf, AMD data center GPU accelerators]
Generated description
AMD data center GPU accelerators are high-performance graphics processors designed to accelerate compute-intensive workloads such as AI, machine learning, and high-performance computing in server and cloud environments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AMD data center GPU accelerators Target entity description: AMD data center GPU accelerators are high-performance graphics processors designed to accelerate compute-intensive workloads such as AI, machine learning, and high-performance computing in server and cloud environments.
-
A.
NVIDIA Tesla data center GPUs
NVIDIA Tesla data center GPUs are high-performance graphics processing units designed for accelerated computing workloads such as AI, machine learning, and high-performance computing in server and data center environments.
-
B.
AMD Radeon GCN-based GPU
The AMD Radeon GCN-based GPU is a graphics processor architecture from AMD’s Graphics Core Next family, widely used in gaming consoles and PCs for efficient, parallel graphics and compute performance.
-
C.
AMD TeraScale architecture
AMD TeraScale architecture is a previous-generation GPU microarchitecture from AMD used in earlier Radeon graphics cards, known for introducing a unified shader design before being succeeded by the GCN architecture.
-
D.
AMD Radeon GPUs
AMD Radeon GPUs are a family of graphics processing units from AMD designed for gaming, professional visualization, and compute workloads, competing directly with NVIDIA’s GeForce and other discrete graphics solutions.
-
E.
AMD Radeon RX Vega series
The AMD Radeon RX Vega series is a family of high-end graphics cards based on AMD’s Vega architecture, designed for demanding gaming and professional graphics workloads.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69f717f4d80c8190a1a95c0f2c83c563 |
completed | May 3, 2026, 9:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f718b852808190a2a0fb48424bffb0 |
completed | May 3, 2026, 9:43 a.m. |
Created at: April 9, 2026, 9:29 p.m.