Triple
T26378807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qualcomm AI Engine |
E660968
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | on-device AI platform |
C36805
|
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: on-device AI platform Context triple: [Qualcomm AI Engine, instanceOf, on-device AI platform]
-
A.
AI inference server
An AI inference server is a system that hosts trained machine learning models and processes incoming requests to generate predictions or responses in real time.
-
B.
embedded computing platform series
A series of embedded computing platforms is a family of related hardware and software modules designed to provide scalable, application-specific processing, connectivity, and I/O capabilities for integration into dedicated electronic systems.
-
C.
computing platform
chosen
A computing platform is an integrated environment of hardware, operating systems, runtime libraries, and tools that together support the execution and development of software applications.
-
D.
machine learning platform component
A machine learning platform component is a modular software element that provides specific functionality—such as data processing, model training, deployment, or monitoring—within an integrated ML lifecycle system.
-
E.
Internet of Things platform
An Internet of Things platform is an integrated software and hardware environment that connects, manages, and analyzes data from distributed IoT devices to enable monitoring, control, and automation of physical systems.
- F. None of above.
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_69ee812a698881908d6a58265995fa39 |
completed | April 26, 2026, 9:18 p.m. |
Created at: April 26, 2026, 11:03 p.m.