RuOpinionNE-2024：从俄语新闻文本中提取观点三元组

RuOpinionNE-2024: Extraction of Opinion Tuples from Russian News Texts

April 9, 2025

作者: Natalia Loukachevitch, Natalia Tkachenko, Anna Lapanitsyna, Mikhail Tikhomirov, Nicolay Rusnachenko

cs.AI

摘要

本文介绍了从俄罗斯新闻文本中提取结构化观点的对话评估共享任务。该竞赛的任务是从给定句子中提取观点元组，这些元组由情感持有者、其目标、表达方式以及持有者对目标的情感组成。该任务共收到超过100份提交作品。参赛者主要尝试了在零样本、少样本和微调模式下使用大型语言模型。测试集上的最佳结果是通过对大型语言模型进行微调获得的。我们还比较了30种提示和11个拥有3至320亿参数的开源语言模型在1样本和10样本设置下的表现，并找出了最佳模型和提示。

English

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.