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Linglib.Phenomena.ArgumentStructure.Studies.Dowty1991

@cite{dowty-1991} Thematic Proto-Roles and Argument Selection #

Study file connecting the proto-role theory (Theories/Semantics/Events/ProtoRoles.lean) to argument selection phenomena.

Dowty's original flat-counting ASP #

@cite{dowty-1991}'s Argument Selection Principle uses flat counting: the argument with the greatest number of Proto-Agent entailments is subject. The library's default ASP uses lattice comparison (@cite{grimm-2011}, @cite{davis-koenig-2000}), which handles priority and fixes anomalies like arrive. This study file preserves Dowty's original counting-based predictions to document where they succeed and where they diverge from the modern approach.

Key predictions formalized #

@cite{dowty-1991}'s original single-argument ASP (flat counting): an argument selects for subjecthood iff its P-Agent count exceeds its P-Patient count. Superseded by lattice-based outranksForSubject in EntailmentProfile.lean.

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    @cite{dowty-1991}'s between-argument comparison (flat counting): arg1 outranks arg2 for subjecthood iff arg1 has strictly more P-Agent entailments, OR they tie on P-Agent but arg2 has strictly more P-Patient entailments.

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      Corollary 1 (flat counting): neither argument outranks the other → alternation.

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        Verbs like kiss, embrace, marry denote actions requiring volitional involvement of two parties, but only the SUBJECT is entailed to be volitional. This single asymmetric P-Agent entailment predicts the transitive argument configuration.

        "kiss" subject: V+M+IE — volitional, in motion, independently existing.

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          "kiss" object: M+IE only — same minus volition.

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            The collective intransitive ("Kim and Sandy kissed") is predicted: when both participants have symmetric volition, neither outranks.

            Psych verbs come in doublets (like/please, fear/frighten) with reversed argument configurations. Under the stative reading, Experiencer and Stimulus have equal P-Agent scores → alternation is predicted.

            Stative: Experiencer and Stimulus have incomparable P-Agent sets ({S,IE} ⊥ {C,IE}) and equal P-Patient (both 0) → alternation.

            Under inchoative interpretation, the Experiencer enters a new mental state → gains changeOfState (P-Patient entailment a).

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              Inchoative breaks the tie: Stimulus outranks Experiencer for subject because the Experiencer now has more P-Patient → Experiencer is a "better" object → Stimulus is subject. Predicts StimExp frame.

              @cite{dowty-1991} identifies three classes based on CoS distribution across non-subject arguments. When CoS is symmetric (both or neither), alternation is possible. When asymmetric, the CoS argument is fixed as DO.

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                          @cite{dowty-1991} Table 1: the interaction of agentivity (most salient P-Agent property) and telicity (most salient P-Patient property) predicts the unergative/unaccusative split. Only the two "pure" cells are stable; the mixed cells are where cross-linguistic variation occurs.

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                            The key divergence between @cite{dowty-1991}'s flat counting and the modern priority-based ASP. Flat counting gets arrive wrong because it counts movement + IE (2 P-Agent) > changeOfState (1 P-Patient), predicting unergative. The modern ASP correctly identifies arrive as unaccusative because it lacks the priority features (volition, causation).

                            These theorems verify that the canonical verb profiles in ProtoRoles.lean match the entailment profiles stored on the English Fragment verb entries.

                            @cite{grimm-2011}'s agentivity lattice reformulates Dowty's proto-roles with lattice structure and connects them to case assignment. Here we verify that Grimm's lattice predictions are consistent with the ASP predictions above, and that it also resolves the arrive anomaly.

                            Grimm's lattice handles the arrive anomaly: arrive's subject has motion but not instigation → not in the NOM/ERG region. Consistent with the priority-based ASP and Table 1, but not flat counting.