february 2009introduction to semantics1 logic, representation and inference introduction to...
TRANSCRIPT
February 2009 Introduction to Semantics 1
Logic, Representation and Inference
Introduction to Semantics
• What is semantics for?• Role of FOL• Montague Approach
February 2009 Introduction to Semantics 2
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.
February 2009 Introduction to Semantics 3
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
February 2009 Introduction to Semantics 4
Different Kinds of MeaningX 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
February 2009 Introduction to Semantics 5
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.
February 2009 Introduction to Semantics 6
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
February 2009 Introduction to Semantics 7
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.
February 2009 Introduction to Semantics 8
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?
February 2009 Introduction to Semantics 9
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.
February 2009 Introduction to Semantics 10
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.
February 2009 Introduction to Semantics 11
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)
February 2009 Introduction to Semantics 12
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.
February 2009 Introduction to Semantics 13
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: ), (, “,”
February 2009 Introduction to Semantics 14
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: ), (, “,”
February 2009 Introduction to Semantics 15
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:
xy teaches(lecturer(x),x) & studies(y,subject(x))xy likes(x,subjectOf(y)) studies(x,y)
February 2009 Introduction to Semantics 16
word POS Logic Representation
csai proper noun individual constant
csai
student common noun 1 place predicate
student(x)
easy adjective 1 place predicate
easy(x)
easy interesting course
adj/noun 1 place predicate
easy(x) & interesting(x) & course(x)
snores intrans verb 1 place predicate
snore (x)
studies trans. verb 2 place predicate
study(x,,y)
gives ditrans verb 3 place pred give(x,y,z)
Logical Form of Phrases
February 2009 Introduction to Semantics 17
Logical Forms of Sentences
• John kicks Fido:
kick(john, fido)
• Every student wrote a program
xy( stud(x) prog(y) & write(x,y))
yx(stud(x) prog(y) & write(x,y))
• Semantic ambiguity related to quantifier scope
February 2009 Introduction to Semantics 18
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
February 2009 Introduction to Semantics 19
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
February 2009 Introduction to Semantics 20
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.
February 2009 Introduction to Semantics 21
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.
February 2009 Introduction to Semantics 22
Swrite(bertrand,principia)
NPbertrand
VPy.write(y,principia)
Vx.y.write(y,x)
NPprincipia
bertrand
writes principia
Parse Tree with Logical Forms