Cross-linguistic dataset of force-flavor combinations in modal elements

Author:

Uegaki Wataru1ORCID,Mucha Anne1,Hannon Ella2,Engels James1,Whibley Fred1

Affiliation:

1. University of Edinburgh

2. University of British Columbia

Abstract

Abstract We present a cross-linguistic dataset of force-flavor combinations in modal elements, which currently contains information on modal semantics in 24 languages and is accessible at https://github.com/EdinburghMeaning​Sciences/modals_database. We discuss theoretical motivations for constructing the dataset, the data collection methodology, as well as the design and the format of the dataset. We also present four case studies using the data: (i) assessment of cross-linguistic generalizations on force/flavor variability; (ii) exploration of generalizations in the lexicalization of negative modality; (iii) investigation of the typology of the morphological encoding of modal strength; and (iv) examination of how future contributes to modality. These case studies illustrate that the dataset supports in-depth assessment of potential cross-linguistic generalizations as well as theory-informed investigations of cross-linguistic variations in modal semantics.

Publisher

John Benjamins Publishing Company

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