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Original scientific paper

https://doi.org/10.22210/govor.2020.37.08

Corpus‐based analysis of spoken narratives. Introducing a corpus and a search tool

Philipp Wasserscheidt orcid id orcid.org/0000-0003-2602-9103 ; Department of Slavic and Hungarian Studies, Humboldt‐University of Berlin Germany
Marija Mandić orcid id orcid.org/0000-0003-4593-212X ; Institute for Balkan Studies, Serbian Academy of Sciences and Arts, Serbia
Nadine Vollstädt orcid id orcid.org/0000-0002-6339-7725 ; Department of Slavic and Hungarian Studies, Humboldt‐University of Berlin Germany
Ana Jovanović orcid id orcid.org/0000-0001-5006-6006 ; Faculty of Philology, University of Belgrade, Serbia
Ivana Tanasijević ; Faculty of Mathematics, University of Belgrade, Serbia
Teodora Vuković ; Department for Slavic Studies, University of Zurich, Switzerland
Ivana Vučina Simić orcid id orcid.org/0000-0003-3339-6059 ; Faculty of Philology, University of Belgrade, Serbia
Uliana Yazhinova ; Department of Slavic and Hungarian Studies, Humboldt‐University of Berlin Germany
Anđelka Zečević ; Faculty of Mathematics, University of Belgrade, Serbia


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Abstract

This paper is concerned with the development of a synchronic corpus containing Serbian spoken narratives and its use for narrative analysis. The corpus (CRONUS – Corpus for the Research On Narratives and their Use in Speech) is optimised to study the structure and use of this discourse genre. First, data sources are presented, followed by corpus creation and access. The semi-spontaneous spoken narratives were orthographically transcribed, and the corpus deeply annotated, with special emphasis on the annotation of narrative sections following Labov’s approach and the annotation of argument structure constructions in the sense of Construction Grammar. Three case studies demonstrate how morphological and
constructional annotation can be effective for the exploration of narratives.

Keywords

narrative, corpus, spoken language, Serbian, deep annotation

Hrčak ID:

254748

URI

https://hrcak.srce.hr/254748

Publication date:

26.3.2021.

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