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Linglib.Theories.Semantics.Lexical.Verb.Affectedness

Affectedness Hierarchy #

@cite{beavers-2010} @cite{dowty-1991}

The affectedness hierarchy is a projection of @cite{dowty-1991}'s P-Patient entailments onto a four-level total order measuring the strength of truth conditions about change in the affected argument.

As a projection of EntailmentProfile #

profileToDegree projects the 10-Boolean EntailmentProfile onto AffectednessDegree, retaining only the P-Patient features relevant to truth-conditional strength. The projection depends on exactly 4 of the 10 features: changeOfState, incrementalTheme, causallyAffected, and stationary. All 5 P-Agent features and dependentExistence are irrelevant (profileToDegree_depends_only_on_patient).

This is one of three canonical projections of EntailmentProfile:

Each projection preserves different information and serves different grammatical predictions:

ProjectionPreservesUsed for
AgentivityNode4 P-Agent featuresSubject selection, case
AffectednessDegreeP-Patient strengthMAP, direct/oblique
PersistenceLevelPersistence patternCase regions, DOM

Grammatical consequence #

The affectedness hierarchy predicts the Morphosyntactic Alignment Principle (MAP): when an argument alternates between direct and oblique realization, the direct variant has truth conditions at least as strong as the oblique. See Phenomena/ArgumentStructure/Studies/Beavers2010.lean for the empirical verification.

Interface to root semantics #

AffectednessDegree relates to three levels of change-of-state representation in the codebase:

These are NOT the same concept. @cite{beavers-koontz-garboden-2020} show that surface CoS can come from either the root or the template. The projection here operates on the proto-role level, which is the final composed meaning — not the root-level or surface-diagnostic level.

Four degrees of affectedness, defined by increasingly weaker truth conditions about what change — if any — occurs in the event.

Each degree is an existential generalization over the result' relation:

  • quantized: φ → [result'(x, s, g_φ, e)] (specific result state)
  • nonquantized: φ → ∃g[result'(x, s, g, e)] (some change occurred)
  • potential: φ → ◇∃g[result'(x, s, g, e)] (change is possible)
  • unspecified: φ → ∃θ[θ(x, e)] (x merely participates)

The hierarchy forms a total order by truth-conditional entailment: quantized ≥ nonquantized ≥ potential ≥ unspecified.

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      The hierarchy ordering: stronger degrees entail weaker ones.

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        Project an EntailmentProfile onto the affectedness hierarchy.

        This is the canonical P-Patient projection: it retains truth-conditional strength while discarding the specific identity of the entailments.

        The projection depends on exactly 4 of the 10 features:

        • changeOfState and incrementalTheme (distinguish quantized/nonquantized)
        • causallyAffected and stationary (distinguish potential/unspecified)

        All 5 P-Agent features and dependentExistence are irrelevant (profileToDegree_depends_only_on_patient).

        @cite{beavers-2010} Table 5: | Dowty P-Patient | Beavers entailment | |-------------------------|-----------------------| | (a) changeOfState | nonquantized change | | (b) incrementalTheme | totally traversed | | (c) causallyAffected | potential change | | (d) stationary | potential change | | (e) dependentExistence | (irrelevant here) |

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          The projection depends only on {CoS, IT, CA, St}. Profiles agreeing on these four features always map to the same degree. The remaining 6 features (V, S, C, M, IE, DE) are irrelevant.

          This is the forward kernel characterization: sufficient conditions for two profiles to have the same image under profileToDegree.

          Die subject: CoS but no IT → nonquantized (the dying entity undergoes change but not incrementally).