RuOpinionNE-2024：俄语新闻文本中的意见元组提取

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

本文介紹了從俄語新聞文本中提取結構化觀點的對話評估共享任務。該競賽的任務是針對給定句子提取觀點元組；這些元組由情感持有者、其目標、表達方式以及持有者對目標的情感組成。總計，該任務收到了超過100份提交。參與者主要嘗試了在零樣本、少樣本和微調格式下使用大型語言模型。在測試集上取得的最佳結果是通過微調一個大型語言模型獲得的。我們還比較了30種提示和11個開源語言模型，這些模型的參數規模在3到320億之間，在1樣本和10樣本設置下進行了測試，並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.