Triple
T23944256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G programming language |
E602871
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | graphical dataflow programming language |
C20542
|
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 dataflow programming language Context triple: [G programming language, instanceOf, graphical dataflow programming language]
-
A.
graphical programming environment
chosen
A graphical programming environment is a software system that allows users to create, modify, and connect program elements visually (often via drag-and-drop blocks or diagrams) instead of writing traditional text-based code.
-
B.
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.
-
C.
graphical tool
A graphical tool is a software application or component that enables users to create, edit, or manipulate visual elements and diagrams through an interactive graphical interface.
-
D.
functional programming language
A functional programming language is a programming paradigm where computation is treated as the evaluation of mathematical functions, emphasizing immutability, first-class functions, and avoidance of side effects.
-
E.
GPU computing framework
A GPU computing framework is a software platform that enables developers to write, manage, and optimize parallel programs that execute on graphics processing units for high-performance computation.
- 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_69e2953e4924819093f1c24c03476b42 |
completed | April 17, 2026, 8:17 p.m. |
Created at: April 17, 2026, 9:11 p.m.