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Contexts for Quantification

                                    Valeria de Paiva

                                        Stanford


                                      April, 2011




Valeria de Paiva (Stanford)               C4Q              April, 2011   1 / 28
Introduction


Natural logic: what we want
Many thanks to Larry, Ulrik for slides!




Program
Show that significant parts of natural language inference can be
carried out in easy, mathematically characterized logical systems.

Whenever possible, to obtain complete axiomatizations,
because the resulting logical systems are likely to be interesting.

To work using all tools of fields like
proof theory, (finite) model theory, algebraic logic,
and complexity theory...



   Valeria de Paiva (Stanford)                       C4Q        April, 2011   2 / 28
Introduction


Introduction

Logic is a cake that can be cut many ways.




This work presents the logical system TIL (for textual inference logic),
a formalization of the AI system Bridge developed in PARC.


 Valeria de Paiva (Stanford)              C4Q                  April, 2011   3 / 28
Introduction


Introduction

Previous presentations of TIL described it as a stand alone system,
synthetized from what is produced by the software.
This is applied logic.




Much work has gone and has still has to go into the process of creating
these representations from sentences, but we will not worry about this
process (or how to improve it) here.
Want to see TIL now in the context of the work of van Benthem,
Pratt-Hartmann and especially Moss, as an extension of traditional
syllogistic logic.
 Valeria de Paiva (Stanford)              C4Q                April, 2011   4 / 28
Introduction


Which logic?




     Bridge reads in a sentence s in English and produces a logical
     knowledge representation r for it.
     The collection of all representations forms the system TIL.
     TIL was meant to be kept as close as it was sensible to FOL
     (first-order logic) but from the start we knew that to model natural
     language sentences we wanted intensional ‘concepts’ and ‘contexts’..
     (cf. ‘Preventing Existence’, FOIS’01)




 Valeria de Paiva (Stanford)              C4Q                 April, 2011   5 / 28
Introduction


An Example: “Three boys ate pizzas"
Conceptual Structure:
     subconcept(boy-1,[List1])
     subconcept(eat-3,[List2])
     subconcept(pizza-5,[List3])
     role(ob,eat-3,pizza-5)
     role(sb,eat-3,boy-1)
     role(cardinality-restriction,boy-1,3)
     role(cardinality-restriction,pizza-5,pl)
Contextual Structure:
    context(t)
    instantiable(boy-1,t)
    instantiable(eat-3,t)
    instantiable(pizza-5,t)
    top-context(t)
 Valeria de Paiva (Stanford)              C4Q   April, 2011   6 / 28
Introduction


TIL has concepts, contexts and roles...

Instead of constants and variables like FOL,
TIL has concepts and subconcepts.
The concept boy-1 is a subconcept of one of the concepts in the list of
concepts represented by the synsets in WordNet for boy.




Similarly for the concepts pizza-5 and eat-3.

 Valeria de Paiva (Stanford)              C4Q                April, 2011   7 / 28
Introduction


TIL has concepts, contexts and roles...



     Concepts in TIL are similar to Description Logic concepts.
     They are similar to predicates in FOL,
     but are not always unary predicates.
     Think of ‘eat-3’ above as a collection of ‘eating’ events,
     in which other concepts in our domain participate.
     Have two kinds of concepts, primitive concepts extracted from an
     idealized version of WordNet and constructed concepts, which are
     always sub-concepts of some primitive concept.
     we assume that our concepts are as fine or as coarse as the sentences that we deal with require.




 Valeria de Paiva (Stanford)                        C4Q                                    April, 2011   8 / 28
Introduction


TIL has concepts, contexts and roles...



       Concepts are related to others via roles. Like
           role(ob,eat-3,pizza-5)
           role(sb,eat-3,boy-1)
       The name of the role in question (ob-ject, sb-subject, agent, patient,
       theme, etc...) will not matter for us here.
       Linguists are used to this ‘event semantics’.
       Yes, this is similar to description logics, but not exactly one.
Deciding which roles will be used with which concepts is a major problem in computational linguistics.

We bypass this problem by assuming that roles are assigned in a consistent, coherent and maximally informative way.




  Valeria de Paiva (Stanford)                          C4Q                                     April, 2011    9 / 28
Introduction


TIL has concepts, contexts and roles...
One main difference is contexts and how we use them for e.g. negation.
For example, for the sentence No boys hopped.
Conceptual Structure:
     role(cardinality-restriction,boy-5,no)
     role(sb,hop-6,boy-5)
     subconcept(boy-5,[List1])
     subconcept(hop-6,[List2])
Contextual Structure:
    context(ctx(hop-6)), context(t)
    context-lifting-relation(antiveridical,t,ctx(hop-6))
    context-relation(t,ctx(hop-6),not-29)
    instantiable(boy-5,ctx(hop-6))
    instantiable(hop-6,ctx(hop-6))
    top-context(t)
    uninstantiable(hop-6,t)
 Valeria de Paiva (Stanford)              C4Q              April, 2011   10 / 28
Introduction


TIL has concepts, contexts and roles...



     Contexts here are similar to the formal objects with the same name,
     discussed by J. McCarthy.
     Contexts are used to ‘fence-off’ concepts and corresponding predicates.
     The same mechanism works for negation, disjunction and many
     intensional concepts, like ‘know’, ‘believe’, ‘prevent’, etc..
     Instantiability and uninstantiability are used to deal with quantification
     and existential import.




 Valeria de Paiva (Stanford)              C4Q                  April, 2011   11 / 28
Introduction


Inference in TIL?


     Inference in TIL is very rudimentary.
     We can ‘drop clauses’ like in most event semantics.
     From the sentence Ed walked and Mary talked
     we are able to infer both Ed walked and Mary talked
     by simply forgetting the respective clauses in the original
     representation.
     We can do trivial inferences like identity and we can compose
     derivations:
                                        s→r r→t
                       s→s                  s→t




 Valeria de Paiva (Stanford)              C4Q                  April, 2011   12 / 28
Introduction


How does TIL deal with syllogisms?...
As far as semantics is concerned, very much like Moss’ and MacCartney’s
systems
Example: All boys are mammals
Conceptual Structure:
     role(cardinality-restriction,boy-2,all(pl))
     role(cardinality-restriction,mammal-4,pl)
     role(copula-pred,be-3,mammal-4)
     role(copula-subj,be-3,boy-2)
     subconcept(boy-2,[List1])
     subconcept(mammal-4,[List2])
Contextual Structure:
     context(t)
     instantiable(be-3,t)
     instantiable(boy-2,t)
     instantiable(mammal-4,t)
     top-context(t)
 Valeria de Paiva (Stanford)              C4Q             April, 2011   13 / 28
Introduction


Semantics


Concepts are interpreted as subsets, so

                                       subconcept(boy-2,[List1])
means that the boys we’re talking about
are a subset of all the boys in the universe
in the senses of the word ‘boy’ in Wordnet.
Similarly the eating concept in our sentence is a subset of the eating events
in the universe.
                           subconcept(eat-3,[List])
This is a bit non-intuitive for proper names, but we still use subsets and not individuals.

This semantics agrees with Moss’ description.



  Valeria de Paiva (Stanford)                            C4Q                                  April, 2011   14 / 28
Introduction


Syllogistic Logic of All
Thanks Larry!




Syntax: Start with a collection of unary atoms (for nouns).
The sentences are the expressions All p are q
Semantics: A model M is a collection of sets M ,
and for each noun p we have an interpretation [[p]] ⊆ M .

                            M |= All p are q          iff   [[p]] ⊆ [[q]]
Proof system:

                                               All p are n All n are q
                      All p are p                     All p are q



   Valeria de Paiva (Stanford)                  C4Q                        April, 2011   15 / 28
Introduction


TIL satisfies the rules for All



                                            All p are n All n are q
                    All p are p                    All p are q

Semantically just transitivity of subset containment.
All boys are boys is odd, but not problematic...
For TIL the transitive inference is simply climbing up the concept hierarchy.

                All boys are mammals All mammals are animals
                              All boys are animals




 Valeria de Paiva (Stanford)                 C4Q                      April, 2011   16 / 28
Introduction


Syllogistic Logic of Some


The sentences are the expressions Some p are q
Semantics: A model M is a collection of sets M ,
and for each noun p,q we have an interpretation [[p,q]] ⊆ M .

                     M |= Some p are q             iff      [[p]] ∩ [[q]] = ∅


Proof system:


      Some p are q             Some p are q             All q are n Some p are q
      Some q are p             Some p are p                    Some p are n




 Valeria de Paiva (Stanford)                 C4Q                               April, 2011   17 / 28
Introduction


TIL satisfies the rules for Some




        Some p are q                 Some p are q                 All q are n Some p are q
        Some q are p                 Some p are p                        Some p are n

The semantics is the same as Moss’, intersection of subsets.
The inference relation between ‘all’ and ‘some’ is outsourced.
Our ‘poor man’s inference system’ called Entailment and Contradiction
Detection (ECD), has a table of relationships between
‘cardinality-restrictions’ postulated.
This is useful if you want to keep your logic options open, no need to decide if empty domains...




  Valeria de Paiva (Stanford)                           C4Q                                   April, 2011   18 / 28
Introduction


The languages S and S † with noun-level negation

If one adds complemented atoms on top of
the language of All and Some,
with interpretation via set complement: [[p]] = M  [[p]],

So if one has
                                                            
                         All p are q
                                                            
                                                             
                                                            
                         Some p are q
                                                            
                                                             
                                                             
                  S
                                                             
                                                             
                         All p are q ≡ No p are q
                                                             
                                                             
                                                                 S†
                        
                        
                         Some p are q ≡ Some p aren’t q
                        
                                                             
                                                             
                                                             
                                                             
                                                             
                                                             
                                                             
                                                             
                               Some non-p are non-q
                                                             
                                                             

Things can get strange, as explained by Moss-Hartmann....

 Valeria de Paiva (Stanford)                    C4Q              April, 2011   19 / 28
Introduction


The logical system for S p + names

The language S p is the language of All and Some, with no negation, p for
positive syllogisms.

                                  Some p are q           Some p are q
           All p are p            Some p are p           Some q are p

          All p are n All n are q                      All n are p Some n are q
                 All p are q                                  Some p are q


                               J is M M is F           J is a p J is a q
           J is J                   F is J               Some p are q

          All p are q J is a p                       M is a p J is M
                 J is a q                                 J is a p

 Valeria de Paiva (Stanford)                     C4Q                       April, 2011   20 / 28
Introduction


TIL satisfies S p + names



This corresponds to sentences like
     Jon is Jon,
     Jon is Mary and Mary is Fred entails Fred is Jon,
     Jon is a man and Jon is a doctor entails Some men are doctors,
     All cats are mammals and Jon is a cat entails Jon is a mammal
     Mary is a cat and Jon is Mary entails Jon is a cat.




 Valeria de Paiva (Stanford)              C4Q              April, 2011   21 / 28
Introduction


A picture stolen from Larry...

                                                          g
                                                      rin
                            F OL                 h-Tu
                                             urc
                                           Ch




                  F Omon    F O2                              2 variable FO logic



                            R†                                † adds full N -negation
     Pe
        a
       no
          -F
            reg
             e




                       S†
                             R                                relational syllogistic
                  S≥
                       S           Rp

                             Sp

 Valeria de Paiva (Stanford)                           C4Q                              April, 2011   22 / 28
Introduction


TIL is not about syllogisms or copula...



Event semantics in general is about transitive,
intransitive, ditransitive, etc. verbs.
TIL should be able to deal with S p and Rp and more...
Noun negation should not present problems,
(outsourced again)
but sentential negation is dealt via contexts.
Contexts look like the higher parts of the picture...
Modal and hybrid logic!




 Valeria de Paiva (Stanford)              C4Q            April, 2011   23 / 28
Introduction


Another picture stolen from Larry...

                                                               g
                                                           rin
                            F OL                      h-Tu
                                                  urc
                                                Ch




                  F Omon    F O2        Kn                         2 variable FO logic



                            R†                                     † adds full N -negation
     Pe
        a
       no
          -F
            reg
             e




                       S†
                             R                                     relational syllogistic
                  S≥
                       S           Rp

                             Sp

 Valeria de Paiva (Stanford)                                C4Q                              April, 2011   24 / 28
Introduction


Thinking Differently....




 Valeria de Paiva (Stanford)              C4Q   April, 2011   25 / 28
Introduction


Avi-Francez’05 sequent system


            Γ, x : S x : S
            Γ, x : J is a p y : J is a q
               Γ λx.y : All p are q
            Γ z : All p are q ∆ y : J is a p
                      Γ, ∆ zy : J is a q
            Γ x : J is p ∆ y : J is q
            Γ, ∆      x, y : Some p are q
            Γ m : Some p are q ∆, x : J is a p, y : J is a q   t: S
                           Γ, ∆ let x, y = m in t : S




 Valeria de Paiva (Stanford)              C4Q                  April, 2011   26 / 28
Introduction


Conjectures




TIL =? Kn (Rp )
Must show S maps into TIL properly
Same for R
What about S and R dagger?
TIL maps into FOL− (Crouch), but need to do better...
Decidability?
Monotonicity principles?




 Valeria de Paiva (Stanford)              C4Q           April, 2011   27 / 28
Introduction


Conclusions




TIL defined from representations, linguistic intuitions taken seriously.
Attempts to fit it into the ‘Cinderella’ shoe of traditional logic.
Gains on the combination logic front, already.
Work is only starting...




 Valeria de Paiva (Stanford)              C4Q                 April, 2011   28 / 28

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Contexts for Quantification

  • 1. Contexts for Quantification Valeria de Paiva Stanford April, 2011 Valeria de Paiva (Stanford) C4Q April, 2011 1 / 28
  • 2. Introduction Natural logic: what we want Many thanks to Larry, Ulrik for slides! Program Show that significant parts of natural language inference can be carried out in easy, mathematically characterized logical systems. Whenever possible, to obtain complete axiomatizations, because the resulting logical systems are likely to be interesting. To work using all tools of fields like proof theory, (finite) model theory, algebraic logic, and complexity theory... Valeria de Paiva (Stanford) C4Q April, 2011 2 / 28
  • 3. Introduction Introduction Logic is a cake that can be cut many ways. This work presents the logical system TIL (for textual inference logic), a formalization of the AI system Bridge developed in PARC. Valeria de Paiva (Stanford) C4Q April, 2011 3 / 28
  • 4. Introduction Introduction Previous presentations of TIL described it as a stand alone system, synthetized from what is produced by the software. This is applied logic. Much work has gone and has still has to go into the process of creating these representations from sentences, but we will not worry about this process (or how to improve it) here. Want to see TIL now in the context of the work of van Benthem, Pratt-Hartmann and especially Moss, as an extension of traditional syllogistic logic. Valeria de Paiva (Stanford) C4Q April, 2011 4 / 28
  • 5. Introduction Which logic? Bridge reads in a sentence s in English and produces a logical knowledge representation r for it. The collection of all representations forms the system TIL. TIL was meant to be kept as close as it was sensible to FOL (first-order logic) but from the start we knew that to model natural language sentences we wanted intensional ‘concepts’ and ‘contexts’.. (cf. ‘Preventing Existence’, FOIS’01) Valeria de Paiva (Stanford) C4Q April, 2011 5 / 28
  • 6. Introduction An Example: “Three boys ate pizzas" Conceptual Structure: subconcept(boy-1,[List1]) subconcept(eat-3,[List2]) subconcept(pizza-5,[List3]) role(ob,eat-3,pizza-5) role(sb,eat-3,boy-1) role(cardinality-restriction,boy-1,3) role(cardinality-restriction,pizza-5,pl) Contextual Structure: context(t) instantiable(boy-1,t) instantiable(eat-3,t) instantiable(pizza-5,t) top-context(t) Valeria de Paiva (Stanford) C4Q April, 2011 6 / 28
  • 7. Introduction TIL has concepts, contexts and roles... Instead of constants and variables like FOL, TIL has concepts and subconcepts. The concept boy-1 is a subconcept of one of the concepts in the list of concepts represented by the synsets in WordNet for boy. Similarly for the concepts pizza-5 and eat-3. Valeria de Paiva (Stanford) C4Q April, 2011 7 / 28
  • 8. Introduction TIL has concepts, contexts and roles... Concepts in TIL are similar to Description Logic concepts. They are similar to predicates in FOL, but are not always unary predicates. Think of ‘eat-3’ above as a collection of ‘eating’ events, in which other concepts in our domain participate. Have two kinds of concepts, primitive concepts extracted from an idealized version of WordNet and constructed concepts, which are always sub-concepts of some primitive concept. we assume that our concepts are as fine or as coarse as the sentences that we deal with require. Valeria de Paiva (Stanford) C4Q April, 2011 8 / 28
  • 9. Introduction TIL has concepts, contexts and roles... Concepts are related to others via roles. Like role(ob,eat-3,pizza-5) role(sb,eat-3,boy-1) The name of the role in question (ob-ject, sb-subject, agent, patient, theme, etc...) will not matter for us here. Linguists are used to this ‘event semantics’. Yes, this is similar to description logics, but not exactly one. Deciding which roles will be used with which concepts is a major problem in computational linguistics. We bypass this problem by assuming that roles are assigned in a consistent, coherent and maximally informative way. Valeria de Paiva (Stanford) C4Q April, 2011 9 / 28
  • 10. Introduction TIL has concepts, contexts and roles... One main difference is contexts and how we use them for e.g. negation. For example, for the sentence No boys hopped. Conceptual Structure: role(cardinality-restriction,boy-5,no) role(sb,hop-6,boy-5) subconcept(boy-5,[List1]) subconcept(hop-6,[List2]) Contextual Structure: context(ctx(hop-6)), context(t) context-lifting-relation(antiveridical,t,ctx(hop-6)) context-relation(t,ctx(hop-6),not-29) instantiable(boy-5,ctx(hop-6)) instantiable(hop-6,ctx(hop-6)) top-context(t) uninstantiable(hop-6,t) Valeria de Paiva (Stanford) C4Q April, 2011 10 / 28
  • 11. Introduction TIL has concepts, contexts and roles... Contexts here are similar to the formal objects with the same name, discussed by J. McCarthy. Contexts are used to ‘fence-off’ concepts and corresponding predicates. The same mechanism works for negation, disjunction and many intensional concepts, like ‘know’, ‘believe’, ‘prevent’, etc.. Instantiability and uninstantiability are used to deal with quantification and existential import. Valeria de Paiva (Stanford) C4Q April, 2011 11 / 28
  • 12. Introduction Inference in TIL? Inference in TIL is very rudimentary. We can ‘drop clauses’ like in most event semantics. From the sentence Ed walked and Mary talked we are able to infer both Ed walked and Mary talked by simply forgetting the respective clauses in the original representation. We can do trivial inferences like identity and we can compose derivations: s→r r→t s→s s→t Valeria de Paiva (Stanford) C4Q April, 2011 12 / 28
  • 13. Introduction How does TIL deal with syllogisms?... As far as semantics is concerned, very much like Moss’ and MacCartney’s systems Example: All boys are mammals Conceptual Structure: role(cardinality-restriction,boy-2,all(pl)) role(cardinality-restriction,mammal-4,pl) role(copula-pred,be-3,mammal-4) role(copula-subj,be-3,boy-2) subconcept(boy-2,[List1]) subconcept(mammal-4,[List2]) Contextual Structure: context(t) instantiable(be-3,t) instantiable(boy-2,t) instantiable(mammal-4,t) top-context(t) Valeria de Paiva (Stanford) C4Q April, 2011 13 / 28
  • 14. Introduction Semantics Concepts are interpreted as subsets, so subconcept(boy-2,[List1]) means that the boys we’re talking about are a subset of all the boys in the universe in the senses of the word ‘boy’ in Wordnet. Similarly the eating concept in our sentence is a subset of the eating events in the universe. subconcept(eat-3,[List]) This is a bit non-intuitive for proper names, but we still use subsets and not individuals. This semantics agrees with Moss’ description. Valeria de Paiva (Stanford) C4Q April, 2011 14 / 28
  • 15. Introduction Syllogistic Logic of All Thanks Larry! Syntax: Start with a collection of unary atoms (for nouns). The sentences are the expressions All p are q Semantics: A model M is a collection of sets M , and for each noun p we have an interpretation [[p]] ⊆ M . M |= All p are q iff [[p]] ⊆ [[q]] Proof system: All p are n All n are q All p are p All p are q Valeria de Paiva (Stanford) C4Q April, 2011 15 / 28
  • 16. Introduction TIL satisfies the rules for All All p are n All n are q All p are p All p are q Semantically just transitivity of subset containment. All boys are boys is odd, but not problematic... For TIL the transitive inference is simply climbing up the concept hierarchy. All boys are mammals All mammals are animals All boys are animals Valeria de Paiva (Stanford) C4Q April, 2011 16 / 28
  • 17. Introduction Syllogistic Logic of Some The sentences are the expressions Some p are q Semantics: A model M is a collection of sets M , and for each noun p,q we have an interpretation [[p,q]] ⊆ M . M |= Some p are q iff [[p]] ∩ [[q]] = ∅ Proof system: Some p are q Some p are q All q are n Some p are q Some q are p Some p are p Some p are n Valeria de Paiva (Stanford) C4Q April, 2011 17 / 28
  • 18. Introduction TIL satisfies the rules for Some Some p are q Some p are q All q are n Some p are q Some q are p Some p are p Some p are n The semantics is the same as Moss’, intersection of subsets. The inference relation between ‘all’ and ‘some’ is outsourced. Our ‘poor man’s inference system’ called Entailment and Contradiction Detection (ECD), has a table of relationships between ‘cardinality-restrictions’ postulated. This is useful if you want to keep your logic options open, no need to decide if empty domains... Valeria de Paiva (Stanford) C4Q April, 2011 18 / 28
  • 19. Introduction The languages S and S † with noun-level negation If one adds complemented atoms on top of the language of All and Some, with interpretation via set complement: [[p]] = M [[p]], So if one has    All p are q       Some p are q     S    All p are q ≡ No p are q   S†    Some p are q ≡ Some p aren’t q          Some non-p are non-q   Things can get strange, as explained by Moss-Hartmann.... Valeria de Paiva (Stanford) C4Q April, 2011 19 / 28
  • 20. Introduction The logical system for S p + names The language S p is the language of All and Some, with no negation, p for positive syllogisms. Some p are q Some p are q All p are p Some p are p Some q are p All p are n All n are q All n are p Some n are q All p are q Some p are q J is M M is F J is a p J is a q J is J F is J Some p are q All p are q J is a p M is a p J is M J is a q J is a p Valeria de Paiva (Stanford) C4Q April, 2011 20 / 28
  • 21. Introduction TIL satisfies S p + names This corresponds to sentences like Jon is Jon, Jon is Mary and Mary is Fred entails Fred is Jon, Jon is a man and Jon is a doctor entails Some men are doctors, All cats are mammals and Jon is a cat entails Jon is a mammal Mary is a cat and Jon is Mary entails Jon is a cat. Valeria de Paiva (Stanford) C4Q April, 2011 21 / 28
  • 22. Introduction A picture stolen from Larry... g rin F OL h-Tu urc Ch F Omon F O2 2 variable FO logic R† † adds full N -negation Pe a no -F reg e S† R relational syllogistic S≥ S Rp Sp Valeria de Paiva (Stanford) C4Q April, 2011 22 / 28
  • 23. Introduction TIL is not about syllogisms or copula... Event semantics in general is about transitive, intransitive, ditransitive, etc. verbs. TIL should be able to deal with S p and Rp and more... Noun negation should not present problems, (outsourced again) but sentential negation is dealt via contexts. Contexts look like the higher parts of the picture... Modal and hybrid logic! Valeria de Paiva (Stanford) C4Q April, 2011 23 / 28
  • 24. Introduction Another picture stolen from Larry... g rin F OL h-Tu urc Ch F Omon F O2 Kn 2 variable FO logic R† † adds full N -negation Pe a no -F reg e S† R relational syllogistic S≥ S Rp Sp Valeria de Paiva (Stanford) C4Q April, 2011 24 / 28
  • 25. Introduction Thinking Differently.... Valeria de Paiva (Stanford) C4Q April, 2011 25 / 28
  • 26. Introduction Avi-Francez’05 sequent system Γ, x : S x : S Γ, x : J is a p y : J is a q Γ λx.y : All p are q Γ z : All p are q ∆ y : J is a p Γ, ∆ zy : J is a q Γ x : J is p ∆ y : J is q Γ, ∆ x, y : Some p are q Γ m : Some p are q ∆, x : J is a p, y : J is a q t: S Γ, ∆ let x, y = m in t : S Valeria de Paiva (Stanford) C4Q April, 2011 26 / 28
  • 27. Introduction Conjectures TIL =? Kn (Rp ) Must show S maps into TIL properly Same for R What about S and R dagger? TIL maps into FOL− (Crouch), but need to do better... Decidability? Monotonicity principles? Valeria de Paiva (Stanford) C4Q April, 2011 27 / 28
  • 28. Introduction Conclusions TIL defined from representations, linguistic intuitions taken seriously. Attempts to fit it into the ‘Cinderella’ shoe of traditional logic. Gains on the combination logic front, already. Work is only starting... Valeria de Paiva (Stanford) C4Q April, 2011 28 / 28