LING 364: Introduction to Formal Semantics Lecture 17 March 9th.

Slides:



Advertisements
Similar presentations
Lecture 11: Datalog Tuesday, February 6, Outline Datalog syntax Examples Semantics: –Minimal model –Least fixpoint –They are equivalent Naive evaluation.
Advertisements

LING 388: Language and Computers Sandiway Fong Lecture 5: 9/5.
LING 364: Introduction to Formal Semantics Lecture 24 April 13th.
LING 388: Language and Computers Sandiway Fong Lecture 5: 9/8.
Semantics (Representing Meaning)
LING 364: Introduction to Formal Semantics Lecture 18 March 21st.
Kaplan’s Theory of Indexicals
LING/C SC/PSYC 438/538 Computational Linguistics Sandiway Fong Lecture 13: 10/9.
Answer Set Programming Overview Dr. Rogelio Dávila Pérez Profesor-Investigador División de Posgrado Universidad Autónoma de Guadalajara
9. Sense Properties and stereotypes
LING 388: Language and Computers Sandiway Fong 9/29 Lecture 11.
ISBN Chapter 3 Describing Syntax and Semantics.
LING 364: Introduction to Formal Semantics Lecture 8 February 7th.
LING 581: Advanced Computational Linguistics Lecture Notes April 23rd.
1 Introduction to Computability Theory Lecture15: Reductions Prof. Amos Israeli.
1 Introduction to Computability Theory Lecture12: Reductions Prof. Amos Israeli.
LING 364: Introduction to Formal Semantics Lecture 23 April 11th.
LING 364: Introduction to Formal Semantics Lecture 10 February 14th.
LING 364: Introduction to Formal Semantics Lecture 14 February 28th.
LING 364: Introduction to Formal Semantics Lecture 9 February 9th.
LING 364: Introduction to Formal Semantics
LING 388: Language and Computers Sandiway Fong Lecture 12: 10/5.
LING 364: Introduction to Formal Semantics Lecture 4 January 24th.
CSCI 5582 Fall 2006 CSCI 5582 Artificial Intelligence Lecture 9 Jim Martin.
1 Draft of a Matchmaking Service Chuang liu. 2 Matchmaking Service Matchmaking Service is a service to help service providers to advertising their service.
James Tam Basic Logical Operations (Fascinating) In this section you will learn some basic logical operations and how to evaluate expressions Image from.
LING 364: Introduction to Formal Semantics Lecture 19 March 28th.
LING 364: Introduction to Formal Semantics Lecture 22 April 6th.
LING 364: Introduction to Formal Semantics Lecture 2 January 17th.
CS 106 Introduction to Computer Science I 02 / 11 / 2008 Instructor: Michael Eckmann.
LING 364: Introduction to Formal Semantics Lecture 19 March 20th.
LING 438/538 Computational Linguistics Sandiway Fong Lecture 12: 10/5.
LING 364: Introduction to Formal Semantics Lecture 7 February 2nd.
LING 364: Introduction to Formal Semantics Lecture 16 March 7th.
LING 364: Introduction to Formal Semantics Lecture 3 January 19th.
LING 388 Language and Computers Lecture 18 10/30/03 Sandiway FONG.
CS 454 Theory of Computation Sonoma State University, Fall 2011 Instructor: B. (Ravi) Ravikumar Office: 116 I Darwin Hall Original slides by Vahid and.
LING 364: Introduction to Formal Semantics Lecture 13 February 23rd.
LING 364: Introduction to Formal Semantics Lecture 5 January 26th.
LING 388: Language and Computers Sandiway Fong Lecture 13: 10/10.
LING 364: Introduction to Formal Semantics Lecture 25 April 18th.
LIN1180/LIN5082 Semantics Lecture 3
LING 581: Advanced Computational Linguistics Lecture Notes April 16th.
LING 388: Language and Computers Sandiway Fong Lecture 7.
LING 388: Language and Computers Sandiway Fong Lecture 3.
UNIT 7 DEIXIS AND DEFINITENESS
CT214 – Logical Foundations of Computing Lecture 8 Introduction to Prolog.
Propositional Calculus CS 270: Mathematical Foundations of Computer Science Jeremy Johnson.
Albert Gatt LIN3021 Formal Semantics Lecture 4. In this lecture Compositionality in Natural Langauge revisited: The role of types The typed lambda calculus.
3.2 Semantics. 2 Semantics Attribute Grammars The Meanings of Programs: Semantics Sebesta Chapter 3.
Programming Languages and Design Lecture 3 Semantic Specifications of Programming Languages Instructor: Li Ma Department of Computer Science Texas Southern.
Study Questions for Quiz 1 1. The Concept of Validity (20 points) a. You will be asked to give the two different definitions of validity given in the lecture.
4.1 Proofs and Counterexamples. Even Odd Numbers Find a property that describes each of the following sets E={…, -4, -2, 0, 2, 4, 6, …} O={…, -3, -1,
Propositional Logic Predicate Logic
Lecture 2 (Chapter 2) Introduction to Semantics and Pragmatics.
44220: Database Design & Implementation Conceptual Data Modelling Ian Perry Room: C49 Tel Ext.: 7287
Lecture 7: Foundations of Query Languages Tuesday, January 23, 2001.
MB: 26 Feb 2001CS Lecture 11 Introduction Reading: Read Chapter 1 of Bratko Programming in Logic: Prolog.
Lecture 1 Ling 442.
CT214 – Logical Foundations of Computing Darren Doherty Rm. 311 Dept. of Information Technology NUI Galway
Engineering Design Process. First, let’s review the “Scientific Method” 1.Ask a question 2.Research 3.Procedure/Method 4.Data Observation 5.Conclusion.
LING 581: Advanced Computational Linguistics
CS 4700: Foundations of Artificial Intelligence
CSE 311 Foundations of Computing I
Knowledge Representation
LING 581: Advanced Computational Linguistics
Chapter 10: Mathematical proofs
LING 581: Advanced Computational Linguistics
LING 581: Advanced Computational Linguistics
Introduction To Robot Decision Making
Presentation transcript:

LING 364: Introduction to Formal Semantics Lecture 17 March 9th

Administrivia No class next week –Have a good Spring break! –next lecture: 21st March (in Comm 214)

Last Time we began looking at –Chapter 5: Complexities of Referring Expressions

Today’s Topic Exercises for Chapter 5 Quiz #4 at the end

Last Time Definite NPs –begin with a definite article (“the”) –refer or “point” to some entity (in some world) –Examples the dogthe old man the picture of Mary the woman who Susan knows I met Predicates –cute: cute(X). or λx.x cute –dog: dog(X).or λx.x a dog What is the role played by “the”? –The dog is cutecf. *dog is cute –Semantic function of “the”: “the” is a function (a robot in Chapter 5’s terms) takes a property, e.g. dog(X), and picks out an individual in the world, e.g. dog42 –Example The dog is cute ⇒ The dog(X) is cute(Y) ⇒ dog42 is cute(Y) ⇒ cute(dog42).

Sense and Reference Imagine a world –Shelby is the only dog which lives at Paul’s house Then same truth conditions for: –(1) Shelby is cute –(2) The dog which lives at Paul’s house is cute Imagine a different world –Paul adopted a different dog, Hannibal Then (1) and (2) are not equivalent –(2) The dog which lives at Paul’s house is cute –(2’) Hannibal is cute –The truth of statement (2’) is independent from (1) Conclusion –Shelby and The dog which lives at Paul’s house don’t have the same meaning

Sense and Reference Reference: –a semantic object –e.g. shelby, dog42 Sense: –computes reference –given a definite description and the state of the world, produce the right or “salient” reference –e.g. given definite description: The dog which lives at Paul’s house situation (or world): Shelby is the only dog which lives at Paul’s house compute reference: shelby

Sense and Reference Sense: –computes reference –e.g. given definite description: The dog which lives at Paul’s house situation (or world): Shelby is the only dog which lives at Paul’s house compute reference: shelby Definite description –The dog which lives at Paul’s house –what must be true in the world? must be some X such that 1.dog(X). is true 2.lives_at(X,house(paul)). is true 3.must be only one such X

Exercises Given grammar: (first attempt) –np(M) --> [the], n(M). –np(M) --> name(N), ['''s'], n(M), {saturate1(M,N)}. –np((M1,M2)) --> np(M1), rel_clause(M2), {saturate1(M1,X), saturate1(M2,X)}. –n(dog(_X)) --> [dog]. –n(house(_X)) --> [house]. –name(paul) --> [paul]. –name(mary) --> [mary]. –rel_clause(M) --> [which], subj_s(M). –subj_s(M) --> vp(M). –vp(M) --> v(M), np(Y), {saturate2(M,Y)}. –v(lives_at(_X,_Y)) --> [lives,at]. –saturate1(P,Y) :- arg(1,P,Y). –saturate2(P,Y) :- arg(2,P,Y).

Exercise 1 Given the meaning grammar in the previous slide –How do ask Prolog what the semantics of (1) and (2) (below) are? –(1) the dog –(2) the dog which lives at Paul’s house Queries (1) –?- np(M,[the,dog],[]). (2) –?- np(M,[the,dog,which,lives,at,paul,’\’s’,house],[]).

Exercise 2 Create a world where Shelby is the dog that lives at Paul’s house –Note: use assert/1 to add the relevant facts to the database add facts –dog(shelby). –lives_at(shelby,house(paul)).

Exercise 3 How do we evaluate the meaning of (1) and (2): –(1) the dog –(2) the dog which lives at Paul’s house for the scenario in Exercise 2 [What is incomplete about the meaning grammar so far?] Queries: –?- np(M,[the,dog],[]), call(M). –?- np(M,[the,dog,which,lives,at,paul,’\’s’, house],[]), call(M).

Exercise 4 Question: –What is incomplete about the meaning grammar so far? Answer: –the dog should be unique Question: –show a possible world that contradicts the meaning –Hint: add facts...

Exercise 5 Question: –What is incomplete about the meaning grammar so far? Answer: –the dog should be unique Question: –what semantics is the meaning grammar computing? Answer: –a dog which lives at Paul’s house Let’s modify the grammar...

Exercise 5 Use findall/3 and length/2 –findall(X,P,List). –length(list,N). –?- findall(X,dog(X),List), length(List,1).

Quiz 4 Assuming –s(P) --> name(N), vp(P), {saturate1(P,N)}. –vp(P) --> v(copula), np_pred(P). –np_pred(cute(_X)) --> [cute]. –v(copula) --> [is]. (1) What would you need to add to make this query work? –?- s(M,[shelby,is,cute],[]).

Quiz 4 (2) Describe in words (or implement) What would you need to change to make this query work? –?- s(M,[the,dog,which,lives,at,paul,’\’s’,house,i s,cute],[]).