November 2006Semantics I1 Natural Language Processing Semantics I What is semantics for? Role of FOL Montague Approach

November 2006Semantics I2 Semantics Semantics is the study of the meaning of NL expressions Expressions include sentences, phrases, and sentences. What is the goal of such study? –Provide a workable definition of meaning. –Explain semantic relations between expressions.

November 2006Semantics I3 Examples of Semantic Relations Synonymy –John killed Mary –John caused Mary to die Entailment –John fed his cat –John has a cat Consistency –John is very sick –John is not feeling well –John is very healthy

November 2006Semantics I4 Different Kinds of Meaning X means Y Meaning as definition: –a bachelor means an unmarried man Meaning as intention: –What did John mean by waving? Meaning as reference: "Eiffel Tower " means

November 2006Semantics I5 Workable Definition of Meaning Restrict the scope of semantics. Ignore irony, metaphor etc. Stick to the literal interpretations of expressions rather than metaphorical ones. (My car drinks petrol). Assume that meaning is understood in terms of something concrete.

November 2006Semantics I6 Concrete Semantics Procedural semantics: the meaning of a phrase or sentence is a procedure: “Pick up a big red block” (Winograd 1972) Object–Oriented Semantics: meaning is an instance of a class. Truth-Conditional Semantics

November 2006Semantics I7 Truth Conditional Semantics Key Claim: the meaning of a sentence is identical to the conditions under which it is true. Know the meaning of "Ġianni ate fish for tea" = know exactly how to apply it to the real world and decide whether it is true or false. On this view, one task of semantic theory is to provide a system for identifying the truth conditions of sentences.

November 2006Semantics I8 TCS and Semantic Relations TCS provides a precise account of semantic relations between sentences. Examples: –S1 is synonymous with S2. –S1 entails S2 –S1 is consistent with S2. –S1 is inconsistent with S2. Just like logic! Which logic?

November 2006Semantics I9 NL Semantics: Two Basic Issues How can we automate the process of associating semantic representations with expressions of natural language? How can we use semantic representations of NL expressions to automate the process of drawing inferences? We will focus mainly on first issue.

November 2006Semantics I10 Associating Semantic Representations Automatically Design a semantic representation language. Figure out how to compute the semantic representation of sentences Link this computation to the grammar and lexicon.

November 2006Semantics I11 Semantic Representation Language Logical form (LF) is the name used by logicians (Russell, Carnap etc) to talk about the representation of context- independent meaning. Semantic representation language has to encode the LF. One concrete representation for logical form is first order logic (FOL)

November 2006Semantics I12 Why is FOL a good thing? Has a precise, model-theoretic semantics. If we can translate a NL sentence S into a sentence of FOL, then we have a precise grasp on at least part of the meaning of S. Important inference problems have been studied for FOL. Computational solutions exist for some of them. Hence the strategy of translating into FOL also gives us a handle on inference.

November 2006Semantics I13 Anatomy of FOL Symbols of different types –constant symbols: a,b,c –variable symbols: x, y, z –function symbols: f,g,h –predicate symbols: p,q,r –connectives: &, v,  –quantifiers: ,  –punctuation: ), (, “,”

November 2006Semantics I14 Anatomy of FOL Symbols of different types –constant symbols: csa3180, nlp, mike, alan, rachel, csai –variable symbols: x, y, z –function symbols:lecturerOf, subjectOf –predicate symbols: studies, likes –connectives: &, v,  –quantifiers: ,  –punctuation: ), (, “,”

November 2006Semantics I15 Anatomy of FOL With these symbols we can make expressions of different types –Expressions for referring to things constant: alan, nlp variable: x term: subject(csa3180) –Expressions for stating facts atomic formula: study(alan,csa3180) complex formula: study(alan,csa3180) & teach(mike, csa3180) quantified expression:  x  y teaches(lecturer(x),x) & studies(y,subject(x))  x  y likes(x,subjectOf(y))  studies(x,y)

16 wordPOSLogicRepresentation csaiproper nounindividual constant csai studentcommon noun1 place predicate student(x) easyadjective1 place predicate easy(x) easy interesting course adj/noun1 place predicate easy(x) & interesting(x) & course(x) snoresintrans verb1 place predicate snore (x) studiestrans. verb2 place predicate study(x,,y) givesditrans verb3 place predgive(x,y,z) Logical Form of Phrases

November 2006Semantics I17 Logical Forms of Sentences John kicks Fido: kick(john, fido) Every student wrote a program  x  y( stud(x)  prog(y) & write(x,y))  y  x(stud(x)  prog(y) & write(x,y)) Semantic ambiguity related to quantifier scope

November 2006Semantics I18 Some simple exercises Letvan(x) represent ‘x is a van’, car(x) represent ‘x is a car’, bike(x) represent ‘x is a bike’, exp(x,y) ‘x is more expensive y’, faster(x,y) ‘x is faster than y’. Translate the following formula into natural language: 1.  x (bike(x)   y (car(y)  exp(y,x)) 2.  x  y ((van(x)  bike(y))  faster(x,y)) 3.  z (car(z)   x  y((van(x)  bike(y))  faster(z,x) & faster(z,y) & exp(z,x) & exp(z,y)

November 2006Semantics I19 Building Logical Form Frege’s Principle of Compositionality The POC states that the LF of a complex phrase can be built out of the LFs of the constituent parts. An everyday example of compositionality is the way in which the “meaning” of arithmetic expressions is computed (2+3) * (4/2) = (5 * 2) = 10

November 2006Semantics I20 Compositionality for NL The LF of the whole sentence can be computed from the LF of the subphrases, i.e. Given the syntactic rule X  Y Z. Suppose [Y], [Z] are the LFs of Y, and Z respectively. Then [X] =  ([Y],[Z]) where  is some function for semantic combination

November 2006Semantics I21 Claims of Richard Montague: Each syntax rule is associated with a semantic rule that describes how the LF of the LHS category is composed from the LF of its subconstituents 1:1 correspondence between syntax and semantics (rule-to-rule hypothesis) Functional composition proposed for combining semantic forms. Lambda calculus proposed as the mechanism for describing functions for semantic combination.

November 2006Semantics I22 Sentence Rule Syntactic Rule: S  NP VP Semantic Rule: [S] = [VP]([NP]) i.e. the LF of S is obtained by "applying" the LF of VP to the LF of NP. For this to be possible [VP] must be a function, and [NP] the argument to the function.

November 2006Semantics I23 S write(bertrand,principia) NP bertrand VP y.write(y,principia) V x. y.write(y,x) NP principia bertrand writes principia Parse Tree with Logical Forms