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Structures Informatiques et Logiques pour la Mod elisation Linguistique (MPRI 2.27.1 - second part) Philippe de Groote Inria 2012-2013 Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod elisation Linguistique


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Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2.27.1 - second part)

Philippe de Groote

Inria

2012-2013

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 1 / 41

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Discourse Analysis

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 2 / 41

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Introduction

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 3 / 41

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Introduction

Examples

A man entered the room. He switched on the light. I am the only one in this group who dares to say that I am wrong. Every farmer who owns a donkey beats it. A wolf might come in. It would eat you first. John does not have a car. He would not know where to park it. Either there is no bathroom in this apartment or it is in a funny place. The man who gives his paycheck to his wife is wiser than the man who gives it to his mistress.

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 4 / 41

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Discourse representation theory Discourse representation structures

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 5 / 41

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Discourse representation theory Discourse representation structures

Definition

Terms t ::= v | c Conditions C ::= ⊤ | Pt1 . . . tn | v ˙ =t | v = t | ¬D Strucutures D ::= ({v1, . . . , vn}, {C1, . . . , Cm})

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 6 / 41

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Discourse representation theory Discourse representation structures

Box notation v1 · · · vn C1 . . . Cm

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 7 / 41

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Discourse representation theory Interpretation

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 8 / 41

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Discourse representation theory Interpretation

Interpretation

v1 · · · vn C1 . . . Cm is interpreted as ∃v1 . . . vn.C1 ∧ . . . ∧ Cm

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 9 / 41

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Discourse representation theory Merging

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 10 / 41

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Discourse representation theory Merging

Merging

A man entered the room. He switched on the light

x man x entered the room x

  • y

switched on the light y → x y man x entered the room x y ˙ =x switched on the light y

Every man loves a woman. ?He smiles at her

¬ x man x ¬ y woman y love x y

  • u v

smile at u v → u v ¬ x man x ¬ y woman y love x y smile at u v

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 11 / 41

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Anaphora resolution

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 12 / 41

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Anaphora resolution

Knowledge-poor approach

Peter loves Mary. But she does not love him. It is John whom she

  • loves. He is a nicer guy.

Based on: morphological features, grammatical roles, discourse functions: theme (topic), rheme, ... Signaling the topic: stating it as the subject, using the passive voice — to turn an object into the subject, clefting (it is from Mary that I learned the news), periphrastic constructions (“as for”, “concerning”, “speaking of”, ...), dislocation, a.k.a. topicalization (Mary, I love her).

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 13 / 41

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Anaphora resolution

Knowledge-poor approach + statistical training

The utility (CDVU) shows you a LIST4250, LIST38PP, or LIST3820 file on your terminal for a format similar to that in which it will be printed

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 14 / 41

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Anaphora resolution

Knowledge based approach

John hid Bill’s keys. He was drunk. John hid Bill’s keys. He was playing a joke on him.

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 15 / 41

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Revisiting DRT Left and right contexts

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 16 / 41

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Revisiting DRT Left and right contexts

Typing the left and right contexts

Montague semantics is based on Church’s simple type theory, which provides a full hierarchy of functional types built upon two atomic types: ι, the type of individuals (a.k.a. entities).

  • , the type of propositions (a.k.a. truth values).

We add a third atomic type, γ, which stands for the type of the left contexts. What about the type of the right contexts?

left context

  • right context
  • γ
  • γ → o

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 17 / 41

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Revisiting DRT Left and right contexts

Updating and accessing the context

nil : γ :: : ι → γ → γ sel : γ → ι

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 18 / 41

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Revisiting DRT Semantic interpretation of the sentences

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 19 / 41

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Revisiting DRT Semantic interpretation of the sentences

Semantic interpretation of the sentences

Let s be the syntactic category of sentences. Remember that we intend to abstract our notions of left and right contexts over the meaning of the sentences. [[s]] = γ → (γ → o) → o

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 20 / 41

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Revisiting DRT Semantic interpretation of the sentences

Composition of two sentence interpretations

[[S1. S2]] = λeφ. [[S1]] e (λe′. [[S2]] e′ φ)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 21 / 41

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Revisiting DRT Semantic interpretation of the sentences

Back to DRT and DRSs

Consider a DRS: x1 . . . xn C1 . . . Cm To such a structure, corresponds the following λ-term of type γ → γ → o → o: λeφ. ∃x1 . . . xn. C1 ∧ · · · ∧ Cm ∧ φ e′ where e′ is a context made of e and of the variables x1, . . . , xn.

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 22 / 41

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Revisiting DRT Semantic interpretation of the sentences

Example

John loves Mary. He smiles at her. [[John loves Mary]] = λeφ. love j m ∧ φ (m::j::e) [[He smiles at her]] = λeφ. smile (selhe e) (selher e) ∧ φ e

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 23 / 41

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Revisiting DRT Semantic interpretation of the sentences

λeφ. [[John loves Mary]] e (λe′. [[He smiles at her]] e′ φ) = λeφ. (λeφ. love j m ∧ φ (m::j::e)) e (λe′. [[He smiles at her]] e′ φ) →β λeφ. (λφ. love j m ∧ φ (m::j::e)) (λe′. [[He smiles at her]] e′ φ) →β λeφ. love j m ∧ (λe′. [[He smiles at her]] e′ φ) (m::j::e) →β λeφ. love j m ∧ [[He smiles at her]] (m::j::e) φ = λeφ. love j m ∧ (λeφ. smile (selhe e) (selher e) ∧ φ e) (m::j::e) φ →β λeφ. love j m ∧ (λφ. smile (selhe (m::j::e)) (selher (m::j::e)) ∧ φ (m::j::e)) φ →β λeφ. love j m ∧ smile (selhe (m::j::e)) (selher (m::j::e)) ∧ φ (m::j::e) = λeφ. love j m ∧ smile j (selher (m::j::e)) ∧ φ (m::j::e) = λeφ. love j m ∧ smile j m ∧ φ (m::j::e)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 24 / 41

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Revisiting DRT Semantic interpretation of the syntactic categories

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 25 / 41

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Revisiting DRT Semantic interpretation of the syntactic categories

Montague’s interpretation s =

  • n

= ι → o np = (ι → o) → o may be rephrased as follows: s =

  • (1)

n = ι →s (2) np = (ι →s) →s (3) Replacing (1) with: s = γ → (γ → o) → o we obtain: n = ι → γ → (γ → o) → o np = (ι → γ → (γ → o) → o) → γ → (γ → o) → o

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 26 / 41

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Revisiting DRT Semantic interpretation of the syntactic categories

This interpretation results in handcrafted lexical semantics such as the following: farmer = λxeφ. farmer x ∧ φ e donkey = λxeφ. donkey x ∧ φ e

  • wns = λos. s (λx. o (λyeφ. own x y ∧ φ e))

beats = λos. s (λx. o (λyeφ. beat x y ∧ φ e)) who = λrnxeφ. n x e (λe. r (λψ. ψ x) e φ) a = λnψeφ. ∃x. n x e (λe. ψ x (x::e) φ) every = λnψeφ. (∀x. ¬(n x e (λe. ¬(ψ x (x::e) (λe. ⊤))))) ∧ φ e it = λψeφ. ψ (sel e) e φ ...which might seem a little bit involved.

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 27 / 41

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Type-theoretic dynamic logic Aim

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 28 / 41

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Type-theoretic dynamic logic Aim

Questions

is there a systematic way of obtaining the new lexical semantics from Montague’s? can we find any “modular” presentation of the approach? is there some dynamic logic hidden in the approach?

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 29 / 41

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Type-theoretic dynamic logic Aim

Principles

Let Ω γ → (γ → o) → o. We intend to design a logic acting on propositions of type Ω We share with DRT the two following assumptions: discourse composition is mainly conjunctive (roughly speaking, a discourse consists in the conjunction of its sentences); the main form of quantification is existential (it introduces referential markers). Consequently, our logic will be based on conjunction and existential quantification (defined as primitives). The other connectives will be

  • btained using negation (a third primitive) and de Morgan’s laws.

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 30 / 41

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Type-theoretic dynamic logic Connectives

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 31 / 41

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Type-theoretic dynamic logic Connectives

Formal Framework

We consider a simply-typed λ-calculus, the terms of which are built upon asignature including the following constants: FIRST-ORDER LOGIC ⊤ :

  • (truth)

¬ :

  • → o

(negation) ∧ :

  • → o → o

(conjunction) ∃ : (ι → o) → o (existential quantification) DYNAMIC PRIMITIVES :: : ι → γ → γ (context updating) sel : γ → ι (choice operator)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 32 / 41

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Type-theoretic dynamic logic Connectives

Conjunction

Conjunction is nothing but sentence composition. We therefore define: A V B λeφ. A e (λe. B e φ)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 33 / 41

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Type-theoretic dynamic logic Connectives

Existential quantification

Existential quantification introduces “reference markers”. It is therefore responsible for context updating: E

  • x. P x λeφ. ∃x. P x (x::e) φ

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 34 / 41

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Type-theoretic dynamic logic Connectives

Negation

We do not want the continuation of the discourse to fall into the scope

  • f the negation. Consequently, negation must be defined as follows:

A λeφ. ¬ (A e (λe. ⊤)) ∧ φ e

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 35 / 41

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Type-theoretic dynamic logic Connectives

Implication and Universal Quantification

These are defined using de Morgan’s laws: A B (A V B) A

  • x. P x

E x. (P x)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 36 / 41

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Type-theoretic dynamic logic Embedding of first order logic

1 Introduction 2 Discourse representation theory

Discourse representation structures Interpretation Merging

3 Anaphora resolution 4 Revisiting DRT

Left and right contexts Semantic interpretation of the sentences Semantic interpretation of the syntactic categories

5 Type-theoretic dynamic logic

Aim Connectives Embedding of first order logic

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 37 / 41

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Type-theoretic dynamic logic Embedding of first order logic

Embedding and conservativity

R t1 . . . tn = λeφ. R t1 . . . tn ∧ φ e ¬A = A A ∧ B = A V B ∃x. A = E

  • x. A

This embedding is such that, for every term e of type γ: A ≡ A e (λe. ⊤)

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 38 / 41

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Type-theoretic dynamic logic Embedding of first order logic

Donkey sentence revisited

Montague-like semantic interpretation: farmer = farmer donkey = donkey

  • wns = λOS. S (λx. O (λy. own x y))

beats = λOS. S (λx. O (λy. beat x y)) who = λRQx. Q x ∧ R (λP. P x) a = λPQ. ∃x. P x ∧ Q x every = λPQ. ∀x. P x ⊃ Q x it = ???

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 39 / 41

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Type-theoretic dynamic logic Embedding of first order logic

Dynamic interpretation: farmer = λx. farmer x donkey = λx. donkey x

  • wns = λOS. S (λx. O (λy. own x y))

beats = λOS. S (λx. O (λy. beat x y)) who = λRQx. Q x V R (λP. P x) a = λPQ. E

  • x. P x V Q x

every = λPQ. A

  • x. P x

Q x it = λPeφ. P (sel e) e φ

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 40 / 41

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Type-theoretic dynamic logic Embedding of first order logic

With the dynamic interpretation we have that: beats it (every (who (owns (a donkey)) farmer)) β-reduces to the following term (modulo de Morgan’s laws):

λeφ. (∀x. farmer x ⊃ (∀y. donkey y ⊃ (own x y ⊃ beat x (sel (x::y::e))))) ∧ φ e

that is, assuming that sel is a “perfect” anaphora resolution operator:

λeφ. (∀x. farmer x ⊃ (∀y. donkey y ⊃ (own x y ⊃ beat x y))) ∧ φ e

Philippe de Groote (Inria) Structures Informatiques et Logiques pour la Mod´ elisation Linguistique (MPRI 2012-2013 41 / 41