Triple
T16074541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global workspace theory |
E389949
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computational cognitive architecture |
C28692
|
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: computational cognitive architecture Context triple: [Global workspace theory, instanceOf, computational cognitive architecture]
-
A.
symbolic cognitive architecture
chosen
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.
-
B.
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.
-
C.
cognitive psychologist
A cognitive psychologist is a professional who studies mental processes such as perception, memory, reasoning, language, and problem-solving to understand how people acquire, process, and use information.
-
D.
model of computation
A model of computation is an abstract mathematical framework that defines how algorithms are represented and executed, specifying the rules, operations, and resources available for performing computations.
-
E.
artificial intelligence
Artificial intelligence is a field of computer science focused on creating systems that can perform tasks that typically require human intelligence, such as learning, reasoning, perception, and decision-making.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
Created at: April 10, 2026, 4:57 a.m.