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RuOpinionNE-2024: Extraction of opinion tuples from Russian news texts.

Loukachevitch, N., Tkachenko, N., Lapanitsyna, A., Tikhomirov, M. and Rusnachenko, N., 2025. RuOpinionNE-2024: Extraction of opinion tuples from Russian news texts. In: The 30th Dialogue conference, 23-25 April 2025, Moscow, Russia, 234-244.

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Official URL: https://dialogue-conf.org/digest/digest2025/

DOI: 10.28995/2075-7182-2025-23-234-244

Abstract

In this paper, we introduce the Dialogue Evaluation shared task on extraction of structured opinions from Russian news texts. The task of the contest is to extract opinion tuples for a given sentence; the tuples are composed of a sentiment holder, its target, an expression and sentiment from the holder to the target. In total, the task received more than 100 submissions. The participants experimented mainly with large language models in zero-shot, few-shot and fine-tuning formats. The best result on the test set was obtained with fine-tuning of a large language model. We also compared 30 prompts and 11 open source language models with 3-32 billion parameters in the 1-shot and 10-shot settings and found the best models and prompts.

Item Type:Conference or Workshop Item (Paper)
ISSN:2221-7932
Uncontrolled Keywords:Structured Sentiment Analysis; Opinion Tuples; Named Entity; News Texts
Group:Faculty of Media, Science and Technology
ID Code:42170
Deposited By: Symplectic RT2
Deposited On:02 Sep 2026 14:46
Last Modified:02 Sep 2026 14:46

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