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Künstliche Intelligenz 35(3-4) - Oktober 2021

https://dl.gi.de/handle/20.500.12116/37799
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Auflistung Künstliche Intelligenz 35(3-4) - Oktober 2021 nach Schlagwort "Bayesian statistics"

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  • Zeitschriftenartikel
    Dissertation Abstract: The Syntax, Semantics and Pragmatics of Japanese Addressee-Honorific Markers
    (KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Yamada, Akitaka
    This dissertation is a case study of filling the gap between the two disciplines about human inference systems: theoretical linguistics and statistics. The main linguistic instance examined in this study is honorificity, in particular honorificity encoded by the Japanese addressee-honorific marker (AHM) -mas . Its linguistic properties and its effect on our inference are given a systematic explanation, in such a way that the traditions of statistics and theoretical linguistics are both maximally respected. For the morphosyntax, -mas is distributed in an unexpected position. It is proposed that this is due to an agreement. For the inference, the dynamicity is modeled as a Bayesian update, and the trigger of the update is the denotation amenable to the proposal of the previous linguistic literature.