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

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

URL: http://arxiv.org/abs/2509.11498v4
Date: Fri, 19 Sep 2025 21:27:23 GMT
Title: DeDisCo at the DISRPT 2025 Shared Task: A System for Discourse Relation Classification
Authors: Zhuoxuan Ju, Jingni Wu, Abhishek Purushothama, Amir Zeldes,
Abstract summary: This paper presents DeDisCo, Georgetown University's entry in the DISRPT 2025 shared task on discourse relation classification.<n>We test two approaches, using an mt5-based encoder and a decoder based approach using the openly available Qwen model.<n>Our system achieves a macro-accuracy score of 71.28, and we provide some interpretation and error analysis for our results.
Score: 6.070010259231488
License: http://creativecommons.org/licenses/by/4.0/
Abstract: 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.

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