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Classical negation Patrick D. Elliott November 16, 2020 Logic and - PowerPoint PPT Presentation

Classical negation Patrick D. Elliott November 16, 2020 Logic and Engineering of Natural Language Semantics 17 in a dynamic alternative semantics Links Slides https://patrl.keybase.pub/lenls2020.pdf Draft paper Towards a predictive logic


  1. Classical negation Patrick D. Elliott November 16, 2020 Logic and Engineering of Natural Language Semantics 17 in a dynamic alternative semantics

  2. Links Slides https://patrl.keybase.pub/lenls2020.pdf Draft paper “Towards a predictive logic of anaphora” https://ling.auf.net/lingbuzz/005562 1

  3. Introduction

  4. Roadmap • Dynamic Semantics (ds) as a logic of (singular) anaphora to indefjnites (Heim 1982, Kamp 1981, Groenendijk & Stokhof 1991). • Defjciencies of dynamic approaches: • Empirical wrinkles, with a particular focus on negation and disjunction. • Explanatory adequacy. • A more principled logic of anaphora: Partial Dynamic Alternative Semantics (p-das). • Reigning in p-das in the pragmatic component. 2

  5. Classical motivations Discourse anaphora : (1) Donkey anaphora : (2) 3 A 1 philosopher attended this talk. She 1 was sitting in the back. Everyone who invited a 1 philosopher was relieved that she 1 came.

  6. Defjning characteristics of a dynamic logic Egli’s theorem: (∃ 𝑜 𝜚) ∧ 𝜔 ⇔ ∃ 𝑜 (𝜚 ∧ 𝜔) Egli’s corrolary: (∃ 𝑜 𝜚) → 𝜔 ⇔ ∀ 𝑜 (𝜚 → 𝜔) (desirability of Egli’s corrolary questionable — donkey sentences can have weak, existential readings; see Kanazawa 1994) 4

  7. Varieties of ds two separate traditions. We’ll focus on Dynamic Predicate Logic (dpl); it’s logical properties are well understood, and it constitutes a foundation for much subsequent work in ds (see, e.g., Groenendijk, Stokhof & Veltman 1996 and van den Berg 1996). Without going into too much detail of how it works — there’ll be enough theory-building later — i’ll discuss some empirical problems for dpl and related theories. 5 Many fmavors of ds that fulfjll these desiderata, and at least

  8. Dynamic semantics and its discontents

  9. Negation and accessibility Generalization An indefjnite in the scope of negation is inaccessible as an antecedent for a subsequent pronoun. 6 (3) # I haven’t met any 1 philosopher. She 1 was unwell. (4) # No 1 philosopher attended this talk. She 1 was unwell.

  10. Negation in dpl In dpl, the semantics of negation is tailored to derive this generalization. Without going into the details of the dpl interpretation schema, negation kills any Discourse Referents (drs) in its scope — it’s a destructive operator. Tie logic is such that, once dead, a dr can’t be revived. 7

  11. Double negation in dpl Tiis makes bad predictions (Groenendijk & Stokhof 1991, Krahmer & Muskens 1995, Gotham 2019, etc.). (5) She 1 ’s sitting in the back! dpl doesn’t validate Double Negation Elimination (dne); we want a logic of anaphora that validates dne. 8 It’s not true that no 1 philosopher attended this talk.

  12. Bathrooms Destructive negation in dpl hamstrings the logic in other ways too; consider Partee’s famous “bathroom” sentence. (6) (6) feels like it should be explicable via the logic of presupposition satisfaction (Beaver 2001), but due to the problem of dne, this won’t work in a dpl-like system. 9 Either there is no 1 bathroom, or it 1 ’s upstairs.

  13. Disjunction and local contexts In other words, we want to explain the anaphoric bathroom sentence in terms of the following: (7) Either there is no bathroom, or it 1 ’s upstairs. Tie treatment of negation in dpl — although motivated by accessibility generalizations — precludes this move. 10 there isn’t no 1 bathroom and

  14. Explanatory adequacy and dpl In dpl, the semantics of the logical connectives is tailored to account for generalizations about where anaphora are licensed. e.g., it’s built into the meaning of conjunction that the fjrst conjunct is processed before the second. (8) a. Unlike in the domain of presupposition projection, there are basically no competing approaches with the same of better empirical predictions. 11 Someone 1 arrived already and she 1 ’s outside. b. # She 1 ’s outside and someone 1 arrived already.

  15. Towards a predictive dynamic logic Tie empirical problem of negation, and the conceptual issues may seem rather removed. As we’ll see however, solving the negation problem will involve adopting a simple, trivalent semantics for negation. Tiis will give us a direction to pursue. In the following, i’ll outline a new, predictive dynamic logic, extending dpl. I’ll dub this logic Partial Dynamic Alternative Semantics (p-das). 12

  16. Partial Dynamic Alternative Semantics

  17. Foundations Like Groenendijk & Stokhof, we’ll give a dynamic interpretation for a simple predicate calculus, with natural numbers as variable symbols, and a priveleged tautology 𝜁 𝑜 . We’ll treat sentential meanings as mappings from assignments, to truth-value assignment pairs (an enrichment of dpl meanings). Tie truth-functional substract will be trivalent , so we’ll pair output assignments with one of three truth-values, true ( ⊤ ), false ( ⊥ ), and maybe ( # ). 13

  18. Partial assignments We assume throughout that assignments are partial functions: ℕ ↦ 𝐸 . In p-das, a pronoun indexed 𝑜 (translated as variables) will induce a presupposition that 𝑜 is defjned at the input assignment. We encode using Beaver’s (2001) 𝜀− operator. 𝜀 1 1 0 # # # Table 1: Beaver’s (2001) 𝜀 -operator 14

  19. Atomic sentences A monadic predicate with a variable argument: A monadic predicate with a constant argument: Tiese clauses are generalized in an obvious way to 𝑜 -ary predicates and sequences of terms. 15 � 𝑄 𝑜 � 𝑕 ≔ { (𝜀 (𝑜 ∈ dom 𝑕) ∧ 𝑕 𝑜 ∈ 𝐽(𝑄), 𝑕) } � 𝑄 𝑑 � 𝑕 ≔ { 𝐽(𝑑) ∈ 𝐽(𝑄), 𝑕) }

  20. Tie initial assignment It will frequently be useful to consider the interpretation of a sentence relative to a privileged initial assignment ( 𝑕 ⊤ ). Tiis is the unique assignment whose domain is ∅ ; it refmects a state in which no variables have been introduced. output the maybe-tagged input: If the input is defjned for 𝑕 , the polarity of the output 16 Relative to 𝑕 ⊤ , a sentence will a free variable will always � 𝑄 1 � 𝑕 ⊤ = { (#, 𝑕 ⊤ ) } depends on whether or not 𝑕 1 is a 𝑄 . � 𝑄 1 � [1↦𝑏] = { (𝑏 ∈ 𝐽(𝑄), [1 ↦ 𝑏]) }

  21. Random assignment In order to model the contribution of indefjnites, we introduce a privileged tautology: random assignment (𝜁 𝑜 ) (van den Berg 1996: ch. 2). Assuming a simple domain of individuals 𝐸 ≔ { 𝑏, 𝑐, 𝑑 } , the efgect of random assignment is illustrated below. 17 � 𝜁 𝑜 � 𝑕 = { (⊤, 𝑕 [𝑜↦𝑦] ) ∣ 𝑦 ∈ 𝐸 } � 𝜁 1 � 𝑕 ⊤ = { (⊤, [1 ↦ 𝑏]), (⊤, [1 ↦ 𝑐]), (⊤, [1 ↦ 𝑑]) }

  22. Presupposition satisfaction Variables introduce indexed presuppositions that are satisfjed by a preceding co-indexed random assignment . Random assignment doesn’t just satisfy the presupposition of subsequent variables, but also induces referential uncertainty relative to a set of alternatives (here: 𝐸 ). In order to take the logic further, we next need to defjne negation and conjunction, but fjrst some important background. 18

  23. Background: Strong Kleene In a logic with three truth-values, ignoring the dynamic scafgolding, what is the semantic contribution of the logical operators? Tie strong Kleene recipe: take the classical, bivalent operators, and their truth/falsity conditions, e.g. • ¬ 𝜚 is true if 𝜚 is false; ¬ 𝜚 is false if 𝜚 is true. • 𝜚 ∧ 𝜔 is true if 𝜚 is true and 𝜔 is true; 𝜚 ∧ 𝜔 is false if either 𝜚 is false or 𝜔 is false. Where these conditions are silent, assume maybe ; this is simply the logic we get if we interpret # as standing in for uncertainty between true and false. 19

  24. Tie Strong Kleene truth-tables for ¬ and ∧ 0 value of the other conjunct. false, the whole conjunction is false, regardless of the truth conditions are silent; this means that if either conjunct is Note: uncertainty projects whenever the truth/falsity Table 2: Negation and conjunction in strong Kleene # 0 # # 0 0 0 # ¬ 𝑡 0 1 1 # 0 1 ∧ 𝑡 # # 1 0 0 1 20

  25. Negation in p-das Negation in p-das is just lifted strong Kleene negation: 21 � ¬ 𝜚 � 𝑕 = { (¬ 𝑡 𝑢, ℎ) ∣ (𝑢, ℎ) ∈ � 𝜚 � 𝑕 }

  26. Positive and negative extensions Dynamic Alternative Semantics (das) will swiftly become diffjcult to reason about. It will be useful to defjne two auxiliary notions: the positive and negative extension of a sentence. Defjnition (Positive and negative extension) For completeness, we can also defjne the maybe extension : 22 � 𝜚 � 𝑕 + = { ℎ ∣ (⊤, ℎ) ∈ � 𝜚 � 𝑕 } � 𝜚 � 𝑕 − = { ℎ ∣ (⊥, ℎ) ∈ � 𝜚 � 𝑕 } � 𝜚 � 𝑕 𝑣 = { ℎ ∣ (#, ℎ) ∈ � 𝜚 � 𝑕 }

  27. Some helpful equivalences + − + N.b. on this basis that dne is valid: 𝑣 We can think of p-das as consisting of two dpl-like logics, 23 useful equivalences: − Based on the defjnition of negation, we already can see some computed in tandem. � ¬ 𝜚 � 𝑕 + = � 𝜚 � 𝑕 � ¬ 𝜚 � 𝑕 − = � 𝜚 � 𝑕 � ¬ 𝜚 � 𝑕 𝑣 = � 𝜚 � 𝑕 � ¬ ¬ 𝜚 � 𝑕 + = � ¬ 𝜚 � 𝑕 − = � 𝜚 � 𝑕 � ¬ ¬ 𝜚 � 𝑕 − = � ¬ 𝜚 � 𝑕 + = � 𝜚 � 𝑕

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