Triple
T10023434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayesian networks |
E200666
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | graphical model |
C26339
|
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: graphical model Context triple: [Bayesian networks, instanceOf, graphical model]
-
A.
statistical model
chosen
A statistical model is a mathematical representation of observed data and underlying random processes, used to describe relationships, make inferences, and generate predictions.
-
B.
deep learning model
A deep learning model is a computational architecture composed of multiple layers of interconnected processing units (neurons) that automatically learn hierarchical representations from data to perform tasks such as classification, prediction, or generation.
-
C.
directed graph
A directed graph is a set of vertices connected by edges that have a specific direction, indicating ordered relationships from one vertex to another.
-
D.
visual modeling language
A visual modeling language is a formal system that uses graphical notations (such as diagrams, symbols, and connectors) to represent, design, and communicate the structure and behavior of complex systems.
-
E.
image generation model
An image generation model is an AI system that creates new images from input data such as text prompts, reference images, or learned patterns, using techniques like deep neural networks and generative modeling.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
Created at: March 30, 2026, 8:53 p.m.