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Developing a Guideline for the Labovian-Structural Analysis of Oral Narratives in Japanese

Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)

DOI:10.63317/3bfu9oz7fze4

Abstract

Narrative analysis is a cornerstone of qualitative research. One leading approach is the Labovian model, but its application is labor-intensive, requiring a holistic, recursive interpretive process that moves back and forth between individual parts of the transcript and the transcript as a whole. Existing Labovian datasets are available only in English, which differs markedly from Japanese in terms of grammar and discourse conventions. To address this gap, we introduce the first systematic guidelines for Labovian narrative analysis of Japanese narrative data. Our guidelines retain all six Labovian categories and extend the framework by providing explicit rules for clause segmentation tailored to Japanese constructions. In addition, our guidelines cover a broader range of clause types and narrative types. Using these guidelines, annotators achieved high agreement in clause segmentation (Fleiss’ kappa = 0.80) and moderate agreement in two structural classification tasks (Krippendorff’s alpha = 0.41 and 0.45, respectively), one of which is slightly higher than that found in prior work despite the use of finer-grained distinctions. This paper describes the Labovian model, the proposed guidelines, the annotation process, and their utility. It concludes by discussing the challenges encountered during the annotation process and the prospects for developing a larger dataset for structural narrative analysis in Japanese qualitative research.

Details

Paper ID
lrec2026-main-138
Pages
pp. 1750-1760
BibKey
watahiki-etal-2026-developing
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-493814-49-4
Conference
The Fifteenth Language Resources and Evaluation Conference (LREC 2026)
Location
Palma, Mallorca, Spain
Date
11 May 2026 16 May 2026

Authors

  • AW

    Amane Watahiki

  • TD

    Tomoki Doi

  • AK

    Akari Kikuchi

  • HO

    Hiroshi Ohata

  • YN

    Yuki I. Nakata

  • TN

    Takuya Niikawa

  • TS

    Taiga Shinozaki

  • HY

    Hitomi Yanaka

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