deep lexical semantics case constructions and framenet
play

Deep Lexical Semantics, Case, Constructions, and FrameNet Jerry R. - PowerPoint PPT Presentation

Deep Lexical Semantics, Case, Constructions, and FrameNet Jerry R. Hobbs USC/ISI Marina del Rey, CA Outline 1. Deep Lexical Semantics 2. Case 3. Constructions 4. FrameNet The Big Picture Observable to be explained utter(i,u,w)


  1. Deep Lexical Semantics, Case, Constructions, and FrameNet Jerry R. Hobbs USC/ISI Marina del Rey, CA

  2. Outline 1. Deep Lexical Semantics 2. Case 3. Constructions 4. FrameNet

  3. The Big Picture Observable to be explained utter(i,u,w) Discourse Coherence Segment(w,e) goal(i,c) Cog'(c,u,e) Syn(w 1 ,e 1 ,-,-) Syn(w 2 ,e 2 ,-,-) CoRel(e 1 ,e 2 ,e) Speaker's Plan: Reasoning about Shared variables so mutual influence Syntax goals and beliefs Logical Form Reasoning with World Knowledge (Local pragmatics: coreference, predicate-strengthening, etc.)

  4. The Big Picture Observable to be explained utter(i,u,w) Segment(w,e) goal(i,c) Cog'(c,u,e) Utterance is an intentional act, intended to cause the hearer u to think about the conventional meaning e of string of words w.

  5. The Big Picture utter(i,u,w) goal(i,c) Cog'(c,u,e) Speaker's Plan: Reasoning about goals and beliefs Pragmatics: Explain why speaker i wants to convey information e

  6. The Big Picture utter(i,u,w) Discourse Coherence Segment(w,e) Explain adjacency of discourse segments Syn(w 1 ,e 1 ,-,-) Syn(w 2 ,e 2 ,-,-) as conveying CoRel(e 1 ,e 2 ,e) coherence relations

  7. The Big Picture Syntax is Syn(w 1 ,e 1 ,-,-) the explanation of adjacency as predicate-argument relations Syntax

  8. The Big Picture Syn(w 1 ,e 1 ,-,-) The best explanation of the occurrence of individual words is that they are intended to convey their conventional meanings. Syntax Logical Form

  9. The Big Picture The best explanation of the logical form Discourse usually solves problems of Coherence coreference, predicate-strengthening, etc. Segment(w,e) goal(i,c) Cog'(c,u,e) Syn(w 1 ,e 1 ,-,-) Syn(w 2 ,e 2 ,-,-) CoRel(e 1 ,e 2 ,e) Speaker's Plan: Reasoning about Shared variables so mutual influence Syntax goals and beliefs Logical Form Reasoning with World Knowledge

  10. The Big Picture Observable to be explained utter(i,u,w) Discourse Coherence Segment(w,e) goal(i,c) Cog'(c,u,e) Syn(w 1 ,e 1 ,-,-) Syn(w 2 ,e 2 ,-,-) CoRel(e 1 ,e 2 ,e) Speaker's Plan: Reasoning about Shared variables so mutual influence Syntax goals and beliefs Logical Form Reasoning with World Knowledge (Local pragmatics: coreference, predicate-strengthening, etc.)

  11. Representation We need a common representation scheme for all these levels: Ontologically promiscuous first-order logic Reify states and events (eventualities) for scope-free logical forms, representational adequacy, etc.

  12. Zoom In Observable to be explained utter(i,u,w) Discourse Coherence Segment(w,e) goal(i,c) Cog'(c,u,e) Syn(w 1 ,e 1 ,-,-) Syn(w 2 ,e 2 ,-,-) CoRel(e 1 ,e 2 ,e) Speaker's Plan: Reasoning about Shared variables so mutual influence Syntax goals and beliefs Logical Form Reasoning with World Knowledge (Local pragmatics: coreference, predicate-strengthening, etc.)

  13. “ Levels ” of Processing S --> NP VP Syntax and Compositional Semantics: Syn(w 1 ,x,N,-,-,-,-) & Syn(w 2 ,e,V,x,N,-,-,-) --> Syn(w 1 w 2 ,e,V,-,-,-,-) Syn is specialization of mean Syn(w 2 ,e,V,x,N,-,-,-) says string or VP w 2 describes situation e provided an NP subject describing x can be found in the right place The rule says if w 1 is an NP describing x and w 2 is a VP describing e (if it had a subject x), then the concatenation w 1 w 2 describes e (and doesn’t need a subject) HPSG converted into FOL

  14. “ Levels ” of Processing Lexical Axioms: kill’(e,x,y) & living-thing(y) --> Syn(“kill”,e,V,x,N,y,N) pred-arg structure selectional spelling or category (incl word sense) constraint phonology subcategorization

  15. Generative Semantics Revisited Lexical Decomposition: kill(x,y) <--> cause(x, become(not(alive(y)))) kill’(e 1 ,x,y) <--> cause’(e 1 ,x,e 2 ) & changeTo’(e 2 ,e 3 ) & not’(e 3 ,e 4 ) & alive’(e 4 ,y) Need this to understand: My roommate killed all my plants. He didn’t water them once while I was gone.

  16. “ Levels ” of Processing Lexical Decomposition: cause’(e,x,become(not(alive(y)))) <--> kill’(e,x,y) Core Theories: water --> nourish; enable(nourish,alive)

  17. “ Levels ” of Processing S --> NP VP Syntax and Compositional Semantics: Syn(w 1 ,x,N,-,-,-,-) & Syn(w 2 ,e,V,x,N,-,-,-) --> Syn(w 1 w 2 ,e,V,-,-,-,-) Lexical Axioms: kill’(e,x,y) & living-thing(y) --> Syn(“kill”,e,V,x,N,y,N) pred-arg structure selectional spelling or category (incl word sense) constraint phonology subcategorization Lexical Decomposition: cause’(e,x,become(not(alive(y)))) <--> kill’(e,x,y) Core Theories: water --> nourish; enable(nourish,alive)

  18. A Sentence Interpreted Syntax: Syn(“My roommate killed my plant.”,e,-,-) He didn’t water them. Syn(“My roommate”,x,-,-) Syn(“killed my plant.”,e,x,-) roommate(x,i) Syn(“killed”,e,x,y) Syn(“my plant.”,y,-,-) Lexical Axioms: kill’(e,x,y) plant(y) Lexical cause(x,become(not(alive(y)))) Decomposition: cause(not(nourish(x,y)),not(alive(y))) Core Theories: cause(not(water(x,y)),not(nourish(x,y)))

  19. Outline 1. Deep Lexical Semantics 2. Case 3. Constructions 4. FrameNet

  20. The Case for Case The relations between predicates and arguments can be classified into a small number of categories. Fillmore ’ s original list: Agentive Instrumental Dative Factitive Locative Objective Comitative Benefactive This proposal had a huge appeal among computational linguists; many lists developed, e.g., Source, Goal, (Inanimate) Cause, Time, etc.

  21. Case and Lexical Decomposition Chris moved the flower pots from the front yard to the back yard with a wheelbarrow. cause ’ (e 1 ,c,e 2 ) & p ’ (e 2 ,w) & cause ’ (e 3 ,e 2 ,e 4 ) & change ’ (e 4 ,e 5 ,e 6 ) & at ’ (e 5 ,p,f) & at ’ (e 6 ,p,b) c causes an event involving w, which causes a change from p being at f to p being at b

  22. Case and Lexical Decomposition Chris moved the flower pots from the front yard to the back yard with a wheelbarrow. cause ’ (e 1 ,c,e 2 ) & p ’ (e 2 ,w) & cause ’ (e 3 ,e 2 ,e 4 ) & change ’ (e 4 ,e 5 ,e 6 ) & at ’ (e 5 ,p,f) & at ’ (e 6 ,p,b) Goal: Agent: end of the entity initiating the change a causal chain Source: Instrument: Object: beginning of an entity mediating (Patient, Theme) the change a causal chain entity undergoing change of state or location

  23. Variations Agent vs. Instrument (vs. Cause): The tornado destroyed the barn. Dative vs. Object: +animate vs. -animate Comitative: cause ’ (e1, {c,d}, e2) & ....

  24. Problem These standard cases or semantic roles seem appropriate exactly insofar as the verb decomposes into a pattern resembling that of “ move ” . “ X lets Y Verb ” : What is X? Agent? not ’ (e 1 ,e 2 ) & cause ’ (e 2 , x, e 3 ) & not ’ (e 3 , e 4 ) x is the entity that doesn ’ t initiate a causal chain “ X outnumbers Y ” : What are X and Y? (Patient and Locative?) ==> In FrameNet case labels are idiosyncratic and only mnemonics Me: Forget the case labels; do the decomposition

  25. Outline 1. Deep Lexical Semantics 2. Case 3. Constructions 4. FrameNet

  26. Constructions A linguistic pattern whose meaning or function is not strictly predictable from the rules of compositional semantics and from the lexical semantics of its parts The majority: A linguistic pattern whose conventionalized meaning or function is among the possible interpretations generated from the rules of compositional semantics and from the lexical semantics of its parts (its motivation), but would not necessarily be chosen as the correct interpretation without the convention

  27. “ Let ’ s ” “ Let us go. ” : You and I should go together. [stilted] You should release us. [victims to kidnapper] “ Let ’ s go. ” : You and I should go together.

  28. utter ’ (e 0 ,i,u, “ Let ’ s go ” ) “ Let ’ s ” Syn( “ Let ’ s go ” ,e,V,u,a,-,-) Interpret “ Let ’ s go ” as a grammatical sentence “ You ” is the addressee in you(u,e 0 ) utterance e 0

  29. utter ’ (e 0 ,i,u, “ Let ’ s go ” ) “ Let ’ s ” Syn( “ Let ’ s go ” ,e,V,u,a,-,-) Contraction Syn( “ Let us go ” ,e,V,u,a,-,-) expanded you(u,e 0 )

  30. utter ’ (e 0 ,i,u, “ Let ’ s go ” ) “ Let ’ s ” Syn( “ Let ’ s go ” ,e,V,u,a,-,-) Syn( “ Let us go ” ,e,V,u,a,-,-) Syn( “ Let ” ,e,V,u,a,y,N,e2,V.Tnsless.OC) Syn( “ us ” ,y,N.Acc,-,-,-,-) Syn( “ go ” ,e2,V.Tnsless,-,-) VP deconcatenated into Verb and Small Clause you(u,e 0 )

  31. utter ’ (e 0 ,i,u, “ Let ’ s go ” ) “ Let ’ s ” Syn( “ Let ’ s go ” ,e,V,u,a,-,-) Syn( “ Let us go ” ,e,V,u,a,-,-) Syn( “ Let ” ,e,V,u,a,y,N,e2,V.Tnsless.OC) Syn( “ us ” ,y,N.Acc,-,-,-,-) Syn( “ go ” ,e2,V.Tnsless,-,-) let ’ (e,u,y,e 2 ) we(y,s,e 0 ) go ’ (e 2 ,y,z 1 ,z 2 ) plural(y,s) “ let ” means let “ go ” means go you(u,e 0 ) “ us ” means we, a set s with type element y (and with i as a member)

  32. utter ’ (e 0 ,i,u, “ Let ’ s go ” ) “ Let ’ s ” Syn( “ Let ’ s go ” ,e,V,u,a,-,-) Syn( “ Let us go ” ,e,V,u,a,-,-) Syn( “ Let ” ,e,V,u,a,y,N,e2,V.Tnsless.OC) Syn( “ us ” ,y,N.Acc,-,-,-,-) Syn( “ go ” ,e2,V.Tnsless,-,-) let ’ (e,u,y,e 2 ) we(y,s,e 0 ) go ’ (e 2 ,y,z 1 ,z 2 ) plural(y,s) you(u,e 0 ) Inclusive “ we ” is one member(u,s) possible interpretation of “ we ”

Recommend


More recommend