Triple
T26242055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lattice sensAI |
E656342
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | edge AI platform |
C51292
|
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: edge AI platform Context triple: [Lattice sensAI, instanceOf, edge AI platform]
-
A.
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.
-
B.
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.
-
C.
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.
-
D.
embedded software platform
An embedded software platform is an integrated collection of software components, tools, and runtime services that provide a standardized environment for developing, deploying, and managing applications on resource-constrained embedded devices.
-
E.
automotive computing platform
An automotive computing platform is an integrated hardware and software system within a vehicle that manages and coordinates functions such as infotainment, driver assistance, connectivity, and vehicle control in a secure and real-time manner.
- 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_69ee5b4c59a881909d9ee4fd013fffd5 |
completed | April 26, 2026, 6:37 p.m. |
Created at: April 26, 2026, 9:03 p.m.