“A Semantic Model for Memory”
E434310
“A Semantic Model for Memory” is a foundational work in cognitive science and artificial intelligence that proposes how human memory can be represented and processed using structured semantic relationships.
All labels observed (1)
| Label | Occurrences |
|---|---|
| “A Semantic Model for Memory” canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4353362 — 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: “A Semantic Model for Memory” Context triple: [Semantic Information Processing, hasPart, “A Semantic Model for Memory”]
-
A.
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.
-
B.
Visual Memory Unit
The Visual Memory Unit is a specialized memory card for the Sega Dreamcast that doubles as a tiny handheld device with its own screen, controls, and mini-games.
-
C.
Unified Theories of Cognition
Unified Theories of Cognition is a comprehensive cognitive science framework proposed by Allen Newell that seeks to explain diverse mental processes—such as problem solving, memory, and learning—within a single, unified theoretical architecture.
-
D.
Metapatterns: Across Space, Time, and Mind
Metapatterns: Across Space, Time, and Mind is a book by biologist Tyler Volk that explores recurring structural and organizational patterns shared across biological, physical, and cognitive systems.
-
E.
Simple Knowledge Organization System
The Simple Knowledge Organization System (SKOS) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and taxonomies on the Semantic Web.
- 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: “A Semantic Model for Memory” Target entity description: “A Semantic Model for Memory” is a foundational work in cognitive science and artificial intelligence that proposes how human memory can be represented and processed using structured semantic relationships.
-
A.
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.
-
B.
Visual Memory Unit
The Visual Memory Unit is a specialized memory card for the Sega Dreamcast that doubles as a tiny handheld device with its own screen, controls, and mini-games.
-
C.
Unified Theories of Cognition
Unified Theories of Cognition is a comprehensive cognitive science framework proposed by Allen Newell that seeks to explain diverse mental processes—such as problem solving, memory, and learning—within a single, unified theoretical architecture.
-
D.
Metapatterns: Across Space, Time, and Mind
Metapatterns: Across Space, Time, and Mind is a book by biologist Tyler Volk that explores recurring structural and organizational patterns shared across biological, physical, and cognitive systems.
-
E.
Simple Knowledge Organization System
The Simple Knowledge Organization System (SKOS) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and taxonomies on the Semantic Web.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence publication
ⓘ
cognitive science publication ⓘ scientific paper ⓘ |
| addresses |
mechanisms for memory retrieval
ⓘ
organization of long-term memory ⓘ representation of concepts ⓘ representation of relationships between concepts ⓘ |
| aimsTo |
bridge human memory and computational models
ⓘ
formalize semantic structure of memory ⓘ |
| assumes |
memory items are interconnected semantically
ⓘ
retrieval depends on semantic structure ⓘ |
| conceptualBasisFor |
later semantic network models
ⓘ
some cognitive architectures for memory ⓘ |
| contributesTo |
computational models of cognition
ⓘ
symbolic AI ⓘ theory of semantic memory ⓘ |
| describes |
how memory can be processed using semantic relationships
ⓘ
how memory can be represented using semantic structures ⓘ |
| emphasizes |
role of meaning in memory organization
ⓘ
structured representation over unstructured storage ⓘ |
| field |
artificial intelligence
ⓘ
cognitive science ⓘ |
| focusesOn |
human memory
ⓘ
knowledge representation ⓘ semantic memory ⓘ structured semantic relationships ⓘ |
| influenced |
AI approaches to memory modeling
ⓘ
later work on cognitive architectures ⓘ later work on semantic networks ⓘ |
| proposes |
model of human memory
ⓘ
semantic representation of memory ⓘ |
| relatedTo |
knowledge representation in AI
ⓘ
memory retrieval mechanisms ⓘ models of human cognition ⓘ semantic processing ⓘ |
| representsMemoryAs |
network of semantic relations
ⓘ
structured set of concepts and links ⓘ |
| typeOfModel |
semantic model
ⓘ
symbolic representation model ⓘ |
| usedIn |
design of semantic network systems
ⓘ
research on AI knowledge bases ⓘ research on human memory ⓘ |
| usesConcept |
associative links
ⓘ
concept nodes ⓘ relations between concepts ⓘ semantic networks ⓘ |
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: “A Semantic Model for Memory” Description of subject: “A Semantic Model for Memory” is a foundational work in cognitive science and artificial intelligence that proposes how human memory can be represented and processed using structured semantic relationships.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.