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1 Special Electives of Comp.Linguistics: Processing Anaphoric Expressions Eleni Miltsakaki AUTH Fall 2005-Lecture 2.

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Presentation on theme: "1 Special Electives of Comp.Linguistics: Processing Anaphoric Expressions Eleni Miltsakaki AUTH Fall 2005-Lecture 2."— Presentation transcript:

1 1 Special Electives of Comp.Linguistics: Processing Anaphoric Expressions Eleni Miltsakaki AUTH Fall 2005-Lecture 2

2 2 Main points from Lecture 1 Anaphoric pronouns –Referring and non-referring pronouns Referring: ref to a contextually salient individual Non-referring: treated as bound variables in sentence semantics Main theoretical approaches –Structural and semantic/pragmatic Fields of study –Linguistics, computational linguistics, psycholinguistics

3 3 Outline of today’s lecture Linguistic semantics: the difference between pronouns interpreted as bound variables vs referring expressions Centering theory

4 4 What is variable binding in linguistic semantics? A variable is something whose denotation varies with the assignment –Traces (1) The man who 1 Mary likes t 1 (2) The man who 2 Mary hates t 2 –Pronouns (3) The man who 1 t 1 talked to the boy who 2 t 2 visited him 1/*2  Note that the interpretation of the traces and the pronoun above does NOT depend on context. It is determined by grammatical rules

5 5 Some terminology Bound variables (4) who 1 Mary likes t 1 Free variables (5) Mary likes t 1 Variable binders (6) A binder c-commands the variable C-command? (I’ll draw a tree on the board to show you what it is)

6 6 Compare with referential pronouns No rule of grammar can give you the interpretation of he in (7) (7) I don’t think anybody here is interested in Smith’s work. He should not be invited.

7 7 Centering theory Basic claim: –some entities in the discourse are more central than others and this affects the choice of referring expressions, i.e., the choice of the speaker to use a full noun phrase or a pronoun etc.

8 8 Some history Centering is the result of two strands of work: –Joshi and Kuhn (1979) Monadic predicate logic –Grosz and Sidner (1986) Linguistic structure Intentional structure Attentional state

9 9 Monadic predicate logic Makes n-ary predicates look monadic Singles out an individual (center) among all those which are arguments to the main predicate It can be proved that inferencing is facilitated in monadic predicate logic Joshi and Kuhn (1979)

10 10 Discourse structure Linguistic structure –Utterances (what is actually said) are the basic elements of linguistic structure Intentional structure –Intentions (discourse purposes) and some basic relations between them (dominance and satisfaction-precedence) Attentional state –Contains information about the objects, properties, relations, intentions that are most salient at any given point

11 Centering Theory CT 1977-1981CT 1986-1995 Complexity of inferencing Almost Monadic PC Attention Reference Coherence Alternatives 1996-2000 Functional Linear Semantic Joshi&Kuhn 1979 Joshi&Weinstein 1981 G&S 1986 GJ&W 1986 G,J& W 1995 Strube&Kuhn 1996 Walker 1996 Stevenson et al 2000

12 12 CT: Basic intuition Perceived difference in coherence due to attention structure: 1. a. John went to his favorite music store to buy a piano b. He had frequented the store for many years. c. He was excited that he could finally buy a piano. d. He arrived just as the store was closing for the day. 2. a. John went to his favorite music store to buy a piano. b. It was a store he had frequented for many years. c. He was excited that he could finally buy a piano. d. It was closing just as John arrived.

13 13 Outline of the Centering model Discourse  segments  utterances Set of forward-looking centers, {Cf1, Cf2…} Preferred center, Cp Backward-looking center, Cb Cf ranking (Sub>Obj>Other) Ordering transitions

14 14 Centering transitions

15 Mary likes Jane. She invited her for dinner. Jane accepted the invitation. > > > MaryJane Sheher Janeinvitation MaryJane Cp=Mary Sheher Cp=Mary JaneInvitation Cp=Jane Mary likes Jane. Cb=Mary She invited her for dinner. Cb=Mary Jane accepted the invitation. Cb=Jane Tr= CONTINUE Tr= SMOOTH-SHIFT Cb(Ui)=Cb(Ui-1)Cb(Ui)≠Cb(Ui-1) Cb(Ui)=Cp(Ui)ContinueSmooth-Shift Cb(Ui)≠Cp(Ui)RetainRough-Shift Applying the Centering model


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