1	COMMUNICATION Chapter 22
2	Outline Communication as Action Formal Grammar Syntactic Analysis (Parsing) Augmented Grammars Semantic Interpretation Ambiguity and Disambiguation Discourse Understanding
3	Communication Communication Intentional exchange of information brought about by the production and perception of signs drawn from a shared system of conventional signs Humans use language to communicate most of what is known about the world The Turing test is based on language
4	Communication as Action Speech act Language production viewed as an action Speaker, hearer, utterance Examples: Query: “Have you smelled the wumpus anywhere?” Inform: “There’s a breeze here in 3 4.” Request: “Please help me carry the gold.” “I could use some help carrying this.” Acknowledge: “OK” Promise: “I’ll shoot the wumpus.”
5	Fundamentals of Language Formal language: A (possibly infinite) set of strings Grammar: A finite set of rules that specifies a language Rewrite rules nonterminal symbols (S, NP, etc) terminal symbols (he) S ® NP VP NP ® Pronoun Pronoun ® he
6	Chomsky Hierarchy Four classes of grammatical formalisms: Recursively enumerable grammars Unrestricted rules: both sides of the rewrite rules can have any number of terminal and nonterminal symbols AB ® C Context-sensitive grammars The RHS must contain at least as many symbols as the LHS ASB ® AXB Context-free grammars (CFG) LHS is a single nonterminal symbol S ® XYa Regular grammars X ® a X ® aY
7	Component Steps of Communication SPEAKER: Intention Know(H,ØAlive(Wumpus,S₃)) Generation “The wumpus is dead” Synthesis [thaxwahmpaxsihzdehd]
8	Component Steps of Communication HEARER: Perception: “The wumpus is dead” Analysis (Parsing): (Semantic Interpretation): ØAlive(Wumpus, Now) Tired(Wumpus, Now) (Pragmatic Interpretation): ØAlive(Wumpus₁, S₃) Tired(Wumpus₁, S₃)
9	Component Steps of Communication HEARER: Disambiguation: ØAlive(Wumpus₁,S₃) Incorporation: TELL( KB, ØAlive(Wumpus₁,S₃) )
10	Formal Grammar The lexicon for e_o: Noun ® stench \| breeze \| glitter \| wumpus \| pit \| pits \| gold \| … Verb ® is \| see \| smell \| shoot \| stinks \| go \| grab \| turn \| … Adjective ® right \| left \| east \| dead \| back \| smelly \| … Adverb ® here \| there \| nearby \| ahead \| right \| left \| east \| … Pronoun ® me \| you \| I \| it \| … Name ® John \| Mary \| Boston \| Aristotle \| … Article ® the \| a \| an \| … Preposition ® to \| in \| on \| near \| … Conjunction ® and \| or \| but \| … Digit ® 0 \| 1 \| 2 \| 3 \| 4 \| 5 \| 6 \| 7 \| 8 \| 9
11	Formal Grammar The grammar for e_o: S ® NP VP I + feel a breeze \| S Conjunction S I feel a breeze + and + I smell a wumpus NP ® Pronoun I \| Name John \| Noun pits \| Article Noun the + wumpus \| Digit Digit 3 4 \| NP PP the wumpus + to the east \| NP RelClause the wumpus + that is smelly
12	Formal Grammar The grammar for e_o (continued): VP® Verb stinks \| VP NP feel + a breeze \| VP Adjective is + smelly \| VP PP turn + to the east \| VP Adverb go + ahead PP ® Preposition NP to + the east RelClause® that VP that + is smelly
13	Formal Grammar Parts of speech Open class: noun, verb, adjective, adverb Closed class: pronoun, article, preposition, conjunction, … Grammar Overgenerate: “Me go Boston” Undergenerate: “I think the wumpus is smelly”
14	Parse Tree
15	Syntactic Analysis (Parsing) Parsing: The process of finding a parse tree for a given input string Top-down parsing Start with the S symbol and search for a tree that has the words as its leaves Bottom-up parsing Start with the words and search for a tree with root S
16	Trace of Bottom-up Parsing List of nodes Subsequence Rule the wumpus is dead the Article ® the Article wumpus is dead wumpus Noun ® wumpus Article Noun is dead Article Noun NP ® Article Noun NP is dead is Verb ® is NP Verb dead dead Adjective ® dead NP Verb Adjective Verb VP ® Verb NP VP Adjective VP Adjective VP ® VP Adjective NP VP NP VP S ® NP VP S
17	Subjective & Objective Cases Overgeneration: S ® NP VP ® NP VP NP ® NP Verb NP Pronoun Verb NP ® Pronoun Verb Pronoun She loves him her loves he She ran towards him She ran towards he
18	Handling Subjective & Objective Cases S ® NPs VP \| … NP_s ® Pronoun_s \| Name \| Noun \| … NP_o ® Pronoun_o \| Name \| Noun \| … VP ® VP NPo \| … PP ® Preposition NP_o Pronoun_s ® I \| you \| he \| she \| it \| … Pronoun_o ® me \| you \| him \| her \| it \| … Disadvantage: Grammar size grows exponentially
19	Augmented Grammars Handling case, agreement, etc Augment grammar rules to allow parameters on nonterminal categories NP(Subjective) NP(Objective) NP(case)
20	Definite Clause Grammar (DCG) The grammar for e1: S ® NP(Subjective) VP \| … NP(case) ® Pronoun(case) \| Name \| Noun \| … VP ® VP NP(Objective) \| … PP ® Preposition NP(Objective) Pronoun(Subjective) ® I \| you \| he \| she \| it \| … Pronoun(Objective) ® me \| you \| him \| her \| it \| …
21	Definite Clause Grammar (DCG) Each grammar rule is a definite clause in logic: S ® NP VP NP(s1) Ù VP(s2) Þ S(s1 + s2) NP(case) ® Pronoun(case) Pronoun(case, s1) Þ NP(case, s1) DCG enables parsing as logical inference: Top-down parsing is backward chaining Bottom-up parsing is forward chaining
22	Verb Subcategorization
23	Verb Subcategorization S ® NP(Subjective) VP([ ]) VP(subcat) ® Verb(subcat) \| VP(subcat + [NP]) NP(Objective) \| VP(subcat + [Adjective]) Adjective \| VP(subcat + [PP]) PP VP(subcat) ® VP(subcat) PP \| VP(subcat) Adverb Verb([NP,NP]) ® give \| hand \| …
24	Parsing Using Verb Subcategorization
25	Semantic Interpretation Semantics: meaning of utterances First-order logic as the representation language Compositional semantics: meaning of a phrase is composed of meaning of the constituent parts of the phrase
26	Semantic Interpretation Exp(x) ® Exp(x₁) Operator(op) Exp(x₂) { x = Apply(op, x₁, x₂) } Exp(x) ® ( Exp(x) ) Exp(x) ® Number(x) Number(x) ® Digit(x) Number(x) ® Number(x₁) Digit(x₂) { x = 10 ´ x₁ + x₂ } Digit(x) ® x { 0 ≤ x ≤ 9 } Operator(x) ® x { x Î { +, -, ´, ¸ }}
27	Semantic Interpretation
28	Semantic Interpretation John loves Mary Loves(John, Mary) (ly lx Loves(x,y)) (Mary) º lx Loves(x, Mary) (lx Loves(x, Mary)) (John) º Loves(John, Mary) S(rel(obj)) ® NP(obj) VP(rel) VP(rel(obj)) ® Verb(rel) NP(obj) NP(obj) ® Name(obj) Name(John) ® John Name(Mary) ® Mary Verb(ly lx Loves(x,y) ) ® loves
29	Semantic Interpretation
30	Pragmatic Interpretation Adding context-dependent information about the current situation to each candidate semantic interpretation Indexicals: phrases that refer directly to the current situation “I am in Boston today” (“I” refers to speaker and “today” refers to now)
31	Language Generation The same DCG can be used for parsing and generation Parsing: Given: S(sem, [John, loves, Mary]) Return: sem = Loves(John, Mary) Generation: Given: S(Loves(John, Mary), words) Return: words = [John, loves, Mary]
32	Ambiguity Lexical ambiguity “the back of the room” vs. “back up your files” “In the interest of stimulating the economy, the government lowered the interest rate.” Syntactic ambiguity (structural ambiguity) “I smelled a wumpus in 2,2” Semantic ambiguity “the IBM lecture” Pragmatic ambiguity “I’ll meet you next Friday”
33	Metonymy Denotes a concept by naming some other concept closely related to it Examples: Company for company’s spokesperson (“IBM announced a new model”) Author for author’s works (“I read Shakespeare”) Producer for producer’s product (“I drive a Honda”)
34	Metonymy Representation of “IBM announced”
35	Metaphor Refer to concepts using words whose meanings are appropriate to other completely different kinds of concepts Example: corporation-as-person metaphor: Speak of a corporation as if it is a person and can experience emotions, has a mind, etc. “That doesn’t scare Digital, which has grown to be the world’s second-largest computer maker.” “But if the company changed its mind, however, it would do so for investment reasons, the filing said.”
36	Disambiguation
37	Discourse Understanding Discourse: multiple sentences Reference resolution: The interpretation of a pronoun or a definite noun phrase that refers to an object in the world “John flagged down the waiter. He ordered a ham sandwich.” “He” refers to “John” “After John proposed to Mary, they found a preacher and got married. For the honeymoon, they went to Hawaii.” “they”? “the honeymoon”?
38	Discourse Understanding Structure of coherent discourse: Sentences are joined by coherence relations Examples of coherence relations between S1 and S2: Enable or cause: S1 brings about a change of state that causes or enables S2 “I went outside. I drove to school.” Explanation: the reverse of enablement, S2 causes or enables S1 and is an explanation for S1 “I was late for school. I overslept.” Exemplification: S2 is an example of the general principle in S1 “This algorithm reverses a list. The input [A,B,C] is mapped to [C,B,A].” Etc.