Documentation

Linglib.Studies.DegenEtAl2020

[DHG+20]: When Redundancy Is Useful #

[FG12] [DR95] [EBF06] [Gri75] [KD21] [WKM15]

Standard RSA with a Boolean semantics predicts no preference for overmodified referring expressions — if "small" already identifies the target, adding "blue" is literally uninformative. Yet speakers routinely overmodify, more with color than with size. [DHG+20] resolve this by relaxing the semantics to a continuous meaning φ(u, o) ∈ [0,1] (per-word noise channels multiplied over the utterance): redundant modifiers then carry real information, and the color/size asymmetry follows from color channels being less noisy than size channels.

The model is the mathlib-PMF RSA pipeline (RSA.L0OfMeaning / RSA.S1Belief, [FG12]): the literal listener L0(·|u) : PMF World normalises φ, and the speaker S1(·|w) : PMF U is S1(u|w) ∝ L0(w|u)^α · cost(u). With α = 1 and zero cost (fun _ => 1), each prediction is one application of S1Belief_apply_lt_iff_score_lt — the partition cancels, leaving an L0 comparison in ℝ≥0∞.

Main results #

Verified data (prose, per [DHG+20]) #

Effect sizes are documented here, not encoded as Lean data. Exp 1 (§3): main effect of sufficient property β = 3.54, SE = .22; scene-variation × property interaction β = 2.26, SE = .74; BDA-fitted noise (Figure 10) MAP x_color = .88, HDI [.85, .92]; x_size = .79, HDI [.76, .80]; near-zero costs β_c ≈ .02/.03, confirming color > size discrimination and the No-Brevity regime. Exp 2 (§4.3): typicality β = −4.17, informativeness β = −5.56, color-competitor β = 0.71 (all p < .0001); [WKM15] found the same typicality direction (β = −2.36). Exp 3 (§5.2): sub-necessary β = 2.11, basic-vs-super β = .60, typicality β = 4.82, length β = −.95, frequency β = .08 (NS); the BDA fits a substantial length cost (β_L = 2.69), so — unlike modifiers — nominal choice is not in the No-Brevity regime.

Modifier scene (Exp 1) #

Three pins varying in size and colour; the target is the small blue pin.

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      The seven referring expressions (each + implicit "pin"): four single adjectives and three size+colour pairs.

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          The target object.

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            Illustrative channel values (match/mismatch per feature): colour highly reliable, size less so. [DHG+20] estimate continuous semantic values from data rather than stipulating them; these conventional values reproduce the qualitative colour/size asymmetry and are shared by the downstream cs-RSA studies.

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              See colorMatch.

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                noncomputable def DegenEtAl2020.φ :
                UtteranceWorldENNReal

                Continuous meaning φ(u, o) ∈ ℝ≥0∞: a single adjective is its noise channel, a pair the product of its two channels.

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                  noncomputable def DegenEtAl2020.L0 (u : Utterance) :
                  PMF World

                  Literal listener L0(·|u) : PMF World, normalising the continuous meaning.

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                    theorem DegenEtAl2020.L0_small_target :
                    (L0 Utterance.small) target = ENNReal.ofReal (2 / 3)

                    L0(target | "small") = 2/3 — size is sufficient but noisy (not 1).

                    theorem DegenEtAl2020.L0_smallBlue_target :
                    (L0 Utterance.smallBlue) target = ENNReal.ofReal (99 / 124)

                    L0(target | "small blue") = 99/124 — the redundant colour sharpens the channel product.

                    theorem DegenEtAl2020.L0_blue_target :
                    (L0 Utterance.blue) target = ENNReal.ofReal (99 / 199)

                    L0(target | "blue") = 99/199 — colour is redundant (two objects are blue).

                    noncomputable def DegenEtAl2020.S1 (w : World) :

                    Pragmatic speaker S1(·|w) ∝ L0(w|u) (α = 1, zero cost), a PMF Utterance.

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                      Main result: S1 strictly prefers the overmodified "small blue" over the sufficient "small" — overmodification is rational under noisy perception.

                      The sufficient "small" beats the redundant "blue" (the size principle).

                      Boolean baseline #

                      Boolean (zero-noise) meaning: a feature matches or it does not.

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                        noncomputable def DegenEtAl2020.boolL0 (u : Utterance) :
                        PMF World

                        Boolean literal listener: uniform on the extension.

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                          noncomputable def DegenEtAl2020.boolS1 (w : World) :

                          Boolean pragmatic speaker.

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                            The Boolean model shows no overmodification preference: "small" already identifies the target perfectly, so adding "blue" adds nothing.

                            No-Brevity bridge #

                            cs-RSA operates in [DR95]'s No-Brevity regime (zero cost, fitted β_c ≈ 0), and Q1/Q2 are independent sub-maxims — so over-description is Q1 (informativity under noise), not a Q2 violation.

                            Nominal scene (Exp 3): overspecification via typicality #

                            The same mechanism with a typicality meaning for nouns: a graded φ_typ ∈ [0,1] plays the role noise plays for adjectives. Values are illustrative (the paper uses elicited typicality norms): the dalmatian is a very typical dalmatian, a typical dog, a moderate animal.

                            Target dalmatian among a cat and a bird; "dog" is basic-sufficient.

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                                Noun utterances at three taxonomic levels.

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                                    noncomputable def DegenEtAl2020.nomL0 (u : NomUtterance) :

                                    Nominal literal listener.

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                                      L0(dalmatian | "dalmatian") = 95/97 — near-perfect via typicality.

                                      L0(dalmatian | "dog") = 8/9 — the basic term discriminates well.

                                      L0(dalmatian | "animal") = 1/3 — no discrimination.

                                      noncomputable def DegenEtAl2020.nomS1 (w : NomWorld) :

                                      Nominal pragmatic speaker.

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                                        Nominal overspecification: S1 prefers the subordinate "dalmatian" over the sufficient basic "dog" — the noun analogue of csrsa_overmod_preferred.

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                                        noncomputable def DegenEtAl2020.nomBoolL0 (u : NomUtterance) :

                                        Boolean nominal literal listener.

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                                          noncomputable def DegenEtAl2020.nomBoolS1 (w : NomWorld) :

                                          Boolean nominal speaker.

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                                            The unified mechanism #

                                            Capstone: continuous semantics makes both overmodification (Exp 1) and overspecification (Exp 3) rational, while the Boolean model predicts neither — one mechanism, two phenomena, only the meaning function changes.