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DeDisCo at the DISRPT 2025 Shared Task: A System for Discourse Relation Classification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3ARVFA9Q3Z" target="_blank" >RIV/00216208:11320/26:RVFA9Q3Z - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2025.disrpt-1.4/" target="_blank" >https://aclanthology.org/2025.disrpt-1.4/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.18653/v1/2025.disrpt-1.4" target="_blank" >10.18653/v1/2025.disrpt-1.4</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    DeDisCo at the DISRPT 2025 Shared Task: A System for Discourse Relation Classification

  • Original language description

    This paper presents DeDisCo, Georgetown University’s entry in the DISRPT 2025 shared task on discourse relation classification. We test two approaches, using an mt5-based encoder and a decoder based approach using the openly available Qwen model. We also experiment on training with augmented dataset for low-resource languages using matched data translated automatically from English, as well as using some additional linguistic features inspired by entries in previous editions of the Shared Task. Our system achieves a macro-accuracy score of 71.28, and we provide some interpretation and error analysis for our results.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 4th Shared Task on Discourse Relation Parsing and Treebanking (DISRPT 2025)

  • ISBN

    979-8-89176-344-9

  • ISSN

  • e-ISSN

  • Number of pages

    15

  • Pages from-to

    48-62

  • Publisher name

  • Place of publication

  • Event location

    Suzhou, China

  • Event date

    Jan 1, 2026

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article