Triple
T34101006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Model Human Processor |
E874568
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cognitive engineering framework |
C45947
|
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: cognitive engineering framework Context triple: [Model Human Processor, instanceOf, cognitive engineering framework]
-
A.
theoretical approach in cognitive science
chosen
A theoretical approach in cognitive science is a coherent framework of concepts, assumptions, and principles used to explain, model, and predict cognitive processes such as perception, memory, language, and reasoning.
-
B.
symbolic cognitive architecture
A symbolic cognitive architecture is a computational framework that models human-like cognition using explicit, manipulable symbols and rule-based processes to represent and transform knowledge.
-
C.
GOMS family model
The GOMS family model is a set of cognitive modeling techniques that describe and predict user interaction with systems by decomposing tasks into goals, operators, methods, and selection rules.
-
D.
human factors research laboratory
A human factors research laboratory is a specialized facility where researchers study how people interact with systems, products, and environments to optimize safety, performance, and user experience.
-
E.
cognitive science research center
A cognitive science research center is an interdisciplinary institution that investigates the nature of mind, intelligence, and cognition through collaborative studies in psychology, neuroscience, computer science, linguistics, philosophy, and related fields.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 1:53 a.m.