Possible Word Representation
- 1. Possible Word Representation Prof. Neeraj Bhargava Kapil Chauhan Department of Computer Science School of Engineering & Systems Sciences MDS University, Ajmer
- 2. Outline Text Semantics Representation Choosing representation Some General Representations What is a logic ? Propositional Logic Predicate logic
- 3. Text Semantics • In Natural Language Processing (NLP), semantics is concerned with the meanings of texts. • There are two main approaches: • Propositional or formal semantics: A block of text is to converted into a formula in a logical language, e.g. predicate calculus. • Vector representation. Texts are embedded into a high- dimensional space.
- 4. Representation AI agents deal with knowledge (data) Facts (believe & observe knowledge) Procedures (how to knowledge) Meaning (relate & define knowledge) Right representation is crucial Early realisation in AI Wrong choice can lead to project failure Active research area
- 5. Choosing a Representation For certain problem solving techniques ‘Best’ representation already known Often a requirement of the technique Or a requirement of the programming language (e.g. Prolog) Examples First order theorem proving… first order logic Inductive logic programming… logic programs Neural networks learning… neural networks Some general representation schemes Suitable for many different (and new) AI applications
- 6. Some General Representations Logical Representations Production Rules Semantic Networks • Conceptual graphs, frames Description Logics (see textbook)
- 7. What is a Logic? A language with concrete rules No ambiguity in representation (may be other errors!) Allows unambiguous communication and processing Very unlike natural languages e.g. English Many ways to translate between languages A statement can be represented in different logics And perhaps differently in same logic Expressiveness of a logic How much can we say in this language? Not to be confused with logical reasoning Logics are languages, reasoning is a process (may use logic)
- 8. Syntax and Semantics Syntax Rules for constructing legal sentences in the logic Which symbols we can use (English: letters, punctuation) How we are allowed to combine symbols Semantics How we interpret (read) sentences in the logic Assigns a meaning to each sentence Example: “All lecturers are seven foot tall” A valid sentence (syntax) And we can understand the meaning (semantics) This sentence happens to be false (there is a counterexample)
- 9. Propositional Logic Syntax Propositions, e.g. “it is wet” Connectives: and, or, not, implies, iff (equivalent) Brackets, T (true) and F (false) Semantics (Classical AKA Boolean) Define how connectives affect truth “P and Q” is true if and only if P is true and Q is true Use truth tables to work out the truth of statements
- 10. Predicate Logic Propositional logic combines atoms An atom contains no propositional connectives Have no structure (today_is_wet, john_likes_apples) Predicates allow us to talk about objects Properties: is_wet(today) Relations: likes(john, apples) True or false In predicate logic each atom is a predicate e.g. first order logic, higher-order logic
- 11. Representation & Logic AI wanted “non-logical representations” Production rules Semantic networks Conceptual graphs, frames But all can be expressed in first order logic! Best of both worlds Logical reading ensures representation well-defined Representations specialised for applications Can make reasoning easier, more intuitive
- 12. Assignment Explain predicate and propositional logic with example.