A computational account of virtual travelers in the Montagovian generative lexicon

Lefeuvre-Halftermeyer, Anaïs; Moot, Richard; Retoré, Christian

doi:10.1075/hcp.66.09lef

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…For instance, consider a case we have already discussed: '#The city outlawed smoking in bars and has 500,000 inhabitants'. This exhibits no extensional overlap, since the organisation and the population are not the same entities (as assumed in Lefeuvre-Halftermeyer et al 2019, Vicente 2015 and much other work exploring copredication sense types). In comparison, consider 'The city outlawed smoking in bars and has 500,000 smokers'.…”

Section: A Coherence Model For Copredicationmentioning

confidence: 99%

Linguistic Representation and Processing of Copredication

Murphy¹

2021

Preprint

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This thesis addresses the lexical and psycholinguistic properties of copredication. In particular, it explores its acceptability, frequency, cross-linguistic and electrophysiological features. It proposes a general parsing bias to account for novel acceptability data, through which Complex-Simple predicate orderings are degraded across distinct nominal types relative to the reverse order. This bias, Incremental Semantic Complexity, states that the parser seeks to process linguistic representations in incremental stages of semantic complexity. English and Italian acceptability data are presented which demonstrate that predicate order preferences are based not on sense dominance but rather sense complexity. Initial evidence is presented indicating that pragmatic factors centred on coherence relations can impact copredication acceptability when such copredications host complex (but not simple) predicates. The real-time processing and electrophysiological properties of copredication are also presented, which serve to replicate and ground the acceptability dynamics presented in the thesis.

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Section: A Coherence Model For Copredicationmentioning

confidence: 99%

Linguistic Representation and Processing of Copredication

Murphy¹

2021

Preprint

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Solving the Individuation and Counting Puzzle with $$\lambda $$ -DRT and MGL

Mery

Moot²,

Retoré

2019

New Frontiers in Artificial Intelligence

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Predicate order and coherence in copredication

Murphy

2021

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This article proposes that predicate order and coherence relations are the two major determining factors in copredication licensing, resolving a long-standing puzzle over the criteria for constructing acceptable copredications. The effects of predicate ordering are claimed to be anchored around semantic complexity, such that copredications with semantically Simple-Complex predicate orderings are more acceptable than the reverse. This motivates a parsing bias, termed Incremental Semantic Complexity. Particular ways of implementing this parsing bias are discussed. The effect of predicate coherence is claimed to be anchored around a sense of causality and featural commonality. Lastly, a hierarchy of possible copredications is outlined (the Copredication Hierarchy), helping to delimit the modelling of copredications to a greater extent than has previously been possible.

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A computational account of virtual travelers in the Montagovian generative lexicon

Cited by 3 publications

References 15 publications

Linguistic Representation and Processing of Copredication

Linguistic Representation and Processing of Copredication

Solving the Individuation and Counting Puzzle with $$\lambda $$ -DRT and MGL

Predicate order and coherence in copredication

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