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Linglib.Theories.Semantics.Dynamic.PIP.Phenomena

PIP: Worked Phenomena #

@cite{keshet-abney-2024} @cite{partee-1972} @cite{roberts-1989} @cite{stone-1997}Concrete examples demonstrating how PIP handles the core anaphora puzzles via description-based retrieval over finite models:

  1. Stone's puzzle: "A wolf might come. It would eat you first."
  2. Bathroom sentences: "Either there's no bathroom, or it's upstairs."
  3. Paycheck pronouns: "John spent his paycheck. Bill saved it."

Each example uses a small finite world/entity model with native_decide to verify PIP's predictions.

Stone's puzzle world model.

Three possible worlds:

  • actual: the evaluation world (no wolf present)
  • wolfIn: a world where a wolf comes in
  • noWolf: a world where no wolf comes in
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      The entities: just one wolf.

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          Formula label for "a wolf".

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            Variable for the wolf.

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              Come-in predicate: wolves come in only at wolfIn.

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                Stone's sentence 1: "A wolf might come."

                might(∃^αWolf x. wolf(x) ∧ comeIn(x))

                The existential is inside the modal:

                • x (the wolf) is local — bound by ∃ inside might
                • The world variable is external — bound by might

                Label αWolf records the description "wolf(x) that comes in".

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                  After "A wolf might come in", the label αWolf is registered.

                  This is the crucial property: even though the wolf exists only in possible worlds, the descriptive content "wolf(x)" is available in the discourse state for subsequent anaphora.

                  Stone's sentence 2: "It would eat you first."

                  "It" = DEF_αWolf{x} — retrieves the wolf via its description. "would" = must in the same accessibility relation.

                  The pronoun succeeds because αWolf was registered by sentence 1 and labels survive modal operators.

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                    The full Stone's puzzle discourse: sentence 1; sentence 2.

                    The discourse is well-defined (non-trivially consistent) because:

                    1. Sentence 1 registers αWolf and filters to worlds where a wolf might come in
                    2. Sentence 2 retrieves the wolf via DEF_αWolf and continues in the modal context
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                      After the full discourse, the label is still available. Labels are monotonically accumulated through conjunction, retrieveDef, and would/must because all these operators preserve labels.

                      End-to-end test: Stone's discourse is consistent on a concrete model.

                      After processing "A wolf might come. It would eat you first.", the discourse state is non-empty: the assignment g_wolf (with vWolf ↦ wolf) at the actual world survives the full pipeline:

                      1. might: g_wolf at.actual survives because (g_wolf,.wolfIn) is in the body result (the wolf exists at.wolfIn via existsLabeled)
                      2. retrieveDef αWolf: succeeds because the label was registered
                      3. would/must: g_wolf at.actual survives because modalExpand adds (g_wolf,.wolfIn) and (g_wolf,.noWolf) to the body's input, and the atom predicate (vWolf ≠ ⋆) holds for all of them

                      Without modalExpand, step 3 would fail: must would check accessible worlds.wolfIn/.noWolf but find no pairs there in the body result.

                      Negative test: an assignment with unbound wolf variable does NOT survive Stone's discourse. The existsLabeled in sentence 1 extends assignments with vWolf ↦.some.wolf, and the atom predicate isWolf requires g.indiv vWolf ==.some.wolf. An unbound assignment (vWolf = ⋆) fails this predicate check, so it cannot appear in the body result of might, and is correctly rejected.

                      This confirms the discourse genuinely filters — it's not vacuously accepting all assignments.

                      Bathroom world model.

                      Two possible worlds:

                      • bath: there is a bathroom (upstairs)
                      • noBath: there is no bathroom
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                          The entities.

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                              Label for "a bathroom".

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                                Variable for the bathroom.

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                                  Upstairs predicate: the bathroom is upstairs in the bath world.

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                                    Partee's bathroom sentence: "Either there's no bathroom, or it's upstairs."

                                    PIP analysis: ¬∃^αBath x.bathroom(x) ∨ upstairs(DEF_αBath{x})

                                    1. First disjunct: negation of labeled existential

                                      • The label αBath is registered even under negation
                                      • Records description "bathroom(x)"
                                    2. Second disjunct: uses DEF_αBath to retrieve the bathroom

                                      • The description "bathroom(x)" is available because labels survive negation (the fundamental PIP insight)

                                    This contrasts with standard DPL/DRT where negation blocks accessibility of discourse referents introduced in the negated scope.

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                                      The bathroom label is registered after the first disjunct, even though it's under negation.

                                      End-to-end test: the full bathroom sentence is consistent on a concrete model.

                                      Given a universal input (all assignment-world pairs), the bathroom sentence produces a non-empty output. The witness (g₀,.noBath) survives via the first disjunct (negation): g₀ doesn't bind vBath to any entity, so it's NOT in the existsLabeled output, meaning negation keeps it.

                                      This verifies the full compositional pipeline: disj → negation → existsLabeled → atom (first disjunct) disj → label floating → retrieveDef → atom (second disjunct)

                                      Negative test: a bathroom-bound assignment at the no-bathroom world is rejected by the full bathroom sentence.

                                      At .noBath, both disjuncts fail:

                                      • First (negation): g_bath IS in the existential's output (it matches the isBathroom predicate), so negation removes it
                                      • Second (upstairs): isUpstairs requires w ==.bath, but w = .noBath

                                      This tests the genuine semantic content: the sentence says either there's no bathroom OR the bathroom is upstairs. A bathroom that isn't upstairs violates both conditions.

                                      Paycheck pronouns:

                                      "John spent his paycheck. Bill saved it."

                                      "it" ≠ John's paycheck (which was already spent). "it" = "his paycheck" with "his" re-evaluated for Bill.

                                      PIP analysis:

                                      • "his paycheck" introduces label α with description "paycheck-of(x, possessor)" where possessor is contextually resolved
                                      • "it" = DEF_α{x} — re-evaluates the description relative to the current assignment, where the subject is now Bill

                                      This is the cleanest argument for description-based over value-based anaphora: the pronoun carries a function (λperson. person's paycheck), not a fixed entity.

                                      Value-based account: "it" → John's paycheck → wrong referent Description-based: "it" → "the paycheck of [current subject]" → Bill's paycheck ✓

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                                          Label for the paycheck description.

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                                            Single-world model (paycheck is non-modal).

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                                                Paycheck-of predicate: relates a paycheck to its owner.

                                                The key property: this predicate is relational — it depends on both the paycheck variable and the possessor variable. When the possessor changes (John → Bill), the paycheck changes too.

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                                                  Description-based anaphora correctly predicts the paycheck reading because the description "paycheck-of(x, possessor)" is re-evaluated when the possessor variable changes.

                                                  In a value-based system, "it" would be bound to johnsPaycheck. In PIP, "it" = DEF_α{x} with α = "paycheck-of(x, possessor)", and the possessor variable gets rebound to bill.

                                                  Summation: Σxφ = ⋃{g(x) : g ∈ G, ⟦φ⟧^{M,{g},w*} = 1}

                                                  PIP's formal construct for collecting entity values across assignments. Given a plural context G, a variable x, and a restricting formula φ, summation returns the set of all g(x) values for assignments g that satisfy φ. This is what handles summation pronouns:

                                                  "Every farmer bought a donkey. They paid a lot for them."

                                                  "them" = Σx(donkey(x)) = the set of ALL donkeys across all farmer-donkey pairs in the plural context G.

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                                                    Unfiltered summation: collects ALL values of v across assignments.

                                                    This is a special case of summationFiltered with a trivially true filter.

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                                                      Unfiltered summation is summation with trivial filter.

                                                      The summation set is non-empty when the context is non-empty and the variable is bound (has a non-⋆ value).

                                                      The three systems compared in @cite{keshet-abney-2024}:

                                                      1. Value-based: Pronouns store entity values directly. Works for simple anaphora, fails for modal/negation/paycheck cases.

                                                      2. Description-based (PIP): Pronouns carry formula labels. Handles all cases uniformly.

                                                      3. File-change / DRT: Pronouns access discourse referents. Handles quantifier donkey cases but struggles with modal contexts (requires modal subordination stipulations).

                                                      PIP subsumes the file-change approach: descriptions that happen to pick out a unique entity degenerate to value-based behavior.

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                                                          Phenomena coverage by strategy.

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