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Advanced Semantic Networks for Natural Language Understanding

Explore the intricate world of semantic networks with primitive concepts and proposition-based calculus to decode language meaning. Delve into powerful structures like Quillian's network, Schank's conceptual dependencies, and Simmon's case-based representations. Unravel the complexity of conceptual graphs, frames, and propositional concepts, unlocking the foundations of intelligence architecture and task-handling systems.

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Advanced Semantic Networks for Natural Language Understanding

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  1. Masterman: 100 primitive concepts, 15,000 concepts Wilks: Natural Language system using semantic networks Shapiro: Propositional calculus based semantic network Early Work

  2. Nodes correspond to word concepts with links to other concepts used to define it. Organized into planes, each plane a graph that defines a single meaning of a word. Links are associative and named, and may be multi-arcs (ors) Use to find relationships between pairs of words through graph search. Quillian's network

  3. Four primitive conceptualizations: ACT (actions), PP (objects – picture producers), AA (action modifiers or aiders), PA (picture modifiers or aiders) Fixed set of primitive actions: ATRANS, PTRANS, PROPEL, MOVE, GRASP, INGEST, EXPEL, INGEST, MTRANS, MBUILD, CONC, SPEAK, ATTEND. Schank's Conceptual Dependency

  4. Different kind of links (multi-arcs): actor (agent), attribute, object, recipient, donor, direction, instrumental conceptualization, causality, state of change, possessor, part Claim is that all knowledge can be broken down into this primitive concepts. Used to create canonical forms of natural language expressions. Schank (cont'd)

  5. Based on Filmore's case structure of verbs. Verbs are the main nodes Have actor, object, instrument, location, and time Captures deep structure of sentence Simmon's Case Based Represent.

  6. Used to incorporate real-world, common-sense default knowledge and to organize large amounts of information. Incorporates expected actions and elements. The actual situation may differ. Scripts have the following components: Entry conditions, Results, Props, Roles, and Scenes. Each element is represented by conceptual dep. Scripts (Schank and Abelson)

  7. Amy went out to lunch. She sat at a table and called a waitress, who brought her a menu. She ordered a sandwich. Easy Example

  8. John visited his favorite restaurant on the way to the concert. he was pleased by the bill because he liked Mozart. Hard Example

  9. Frames are structured entities with named slots and attached values. Values may be procedural (think objects). Frames are related to one another. Example slots: ID, relationship to other frames, description of requirements, procedural information, default information, new instance information. Frames support class inheritance. Frames (Minsky)

  10. Two types of nodes: concepts and conceptual relations. Arcs are not labeled – a conceptual relation node appears between two concept nodes instead. Concept nodes may be concrete or abstract objects. Each graph represents a single proposition. A graph may be boxed and used as a node in another graph. Conceptual Graphs (Sowa)

  11. Every concept is of a unique individual of a give type. Each concept box is labeled with a type label. (:) A concept could be a specific, but unnamed individual. (#) A name is different from the object (name conceptual relation) A concept may be an unspecified individual (*). There is a type hierarchy. Conceptual Graphs (cont'd)

  12. The following rules may be used to modify graphs: An exact copy may be made (copy rule). A generic marker may be replaced by an individual marker (restrict). A type may be replaced by a subtype as long as the subtype is consistent with the referent (restrict). Two graphs may be joined by a common concept (join). Conceptual Graphs: Rules

  13. Graphs may be used to represent relations between propositions (causality, time, etc.) A propositional concept is indicated by a box around a conceptual graph and may be used as a node in another graph. Neg and conjunction are conceptual relations. Conceptual graphs have the same expressive power as the predicate calculus. Propositional Concepts

  14. The idea is that intelligence emerges from the interaction of architectures of simpler behaviors. Layered collection of task-handlers which interact with neighboring layers. Each task-handler perceives (input from a lower level), applies a simple set of condition-action production rules, and produces action-orient output (to a higher level). Subsumption Architecture (Brooks)

  15. No global state. Some feedback to lower levels. Example: Machine robot: Three levels – Explore, Wander, Avoid. Brooks (cont'd)

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