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Theory-Driven Statistical Modeling for Semantics & Pragmatics Theoretical linguistics postulates abstract structures that successfully explain key aspects of language, such as semantic meaning. However, the precise relation between abstract theoretical ideas and empirical data from language use is not always straightforward. I propose to empirically test abstract semantic theories through the lens of probabilistic pragmatic modeling using statistical model comparison of theory-driven models which embed semantic ideas as key functional elements. Two case studies are present. One on grammatically generated implicature readings, and one on the logical structure of quantifier meanings
