Model Human Processor
E874568
cognitive architecture
cognitive engineering framework
human information processing model
human–computer interaction model
Model Human Processor is a cognitive engineering framework that models human perception, cognition, and motor behavior as an information-processing system to predict and improve human–computer interaction performance.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Model Human Processor canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T10602350 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Model Human Processor Context triple: [Stuart K. Card, notableWork, Model Human Processor]
-
A.
Goya inference processor
The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
-
B.
Human Understanding
Human Understanding is a philosophical work by Stephen Toulmin that examines the nature of human rationality, reasoning, and the development of knowledge.
-
C.
Intelligence Processing Unit
The Intelligence Processing Unit is a specialized processor architecture designed by Graphcore to accelerate artificial intelligence and machine learning workloads with highly parallel, memory-rich compute.
-
D.
Soar cognitive architecture
The Soar cognitive architecture is a general-purpose framework for modeling and understanding human cognition through unified theories of problem solving, learning, and decision-making.
-
E.
Robust.AI
Robust.AI is a robotics company focused on building practical, intelligent robot systems for real-world environments, co-founded by renowned roboticist Rodney Brooks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Model Human Processor Target entity description: Model Human Processor is a cognitive engineering framework that models human perception, cognition, and motor behavior as an information-processing system to predict and improve human–computer interaction performance.
-
A.
Goya inference processor
The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
-
B.
Human Understanding
Human Understanding is a philosophical work by Stephen Toulmin that examines the nature of human rationality, reasoning, and the development of knowledge.
-
C.
Intelligence Processing Unit
The Intelligence Processing Unit is a specialized processor architecture designed by Graphcore to accelerate artificial intelligence and machine learning workloads with highly parallel, memory-rich compute.
-
D.
Soar cognitive architecture
The Soar cognitive architecture is a general-purpose framework for modeling and understanding human cognition through unified theories of problem solving, learning, and decision-making.
-
E.
Robust.AI
Robust.AI is a robotics company focused on building practical, intelligent robot systems for real-world environments, co-founded by renowned roboticist Rodney Brooks.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
cognitive architecture
ⓘ
cognitive engineering framework ⓘ human information processing model ⓘ human–computer interaction model ⓘ |
| abbreviation | MHP NERFINISHED ⓘ |
| assumes |
memory capacities
ⓘ
perceptual thresholds ⓘ processor cycle times ⓘ |
| basedOn | information processing metaphor ⓘ |
| describedIn | The Psychology of Human-Computer Interaction NERFINISHED ⓘ |
| developedBy |
Allen Newell
NERFINISHED
ⓘ
Stuart K. Card NERFINISHED ⓘ Thomas P. Moran NERFINISHED ⓘ |
| field |
cognitive engineering
ⓘ
cognitive psychology NERFINISHED ⓘ human factors ⓘ human–computer interaction NERFINISHED ⓘ |
| focusesOn |
expert user performance
ⓘ
routine cognitive skills ⓘ |
| goal |
improve human–computer interaction performance
ⓘ
predict task completion time ⓘ |
| hasComponent |
cognitive system
ⓘ
motor system ⓘ perceptual system ⓘ |
| ignores |
individual differences beyond parameter ranges
ⓘ
learning effects ⓘ |
| influenced |
GOMS model
NERFINISHED
ⓘ
Keystroke-Level Model NERFINISHED ⓘ |
| models |
human cognition
ⓘ
human motor behavior ⓘ human perception ⓘ |
| originatedIn | United States NERFINISHED ⓘ |
| parameterType |
cognitive processor cycle time
ⓘ
long-term memory retrieval time ⓘ motor processor cycle time ⓘ perceptual processor cycle time ⓘ short-term memory capacity ⓘ |
| publicationYear | 1983 ⓘ |
| relatedTo |
card-moran-newell HCI framework
NERFINISHED
ⓘ
human information processing theory ⓘ |
| representsHumanAs | information processing system ⓘ |
| timePeriod | late 20th century ⓘ |
| usedFor |
designing user interfaces
ⓘ
evaluating interaction techniques ⓘ keystroke-level modeling ⓘ predicting human performance ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Model Human Processor Description of subject: Model Human Processor is a cognitive engineering framework that models human perception, cognition, and motor behavior as an information-processing system to predict and improve human–computer interaction performance.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.