构建统一观点概念体系，实现观点语义的精准提取与评估
Towards Semantic Integration of Opinions: Unified Opinion Concepts Ontology and Extraction Task
- 提出统一观点概念本体（UOC），整合多角度观点语义
- 设计新抽取任务UOCE，支持更丰富观点表达的识别
- 构建人工扩展标注数据集，适配观点语义评估需求
本文提出统一观点概念（UOC）本体，以在不同表述中整合观点的语义上下文。该本体基于自然语言处理领域广泛研究的观点维度及符号化语义结构，实现观点语义的统一表征。我们进一步提出统一观点概念抽取（UOCE）任务，旨在从文本中提取具有增强表达力的观点。同时，我们构建了一个手动扩展并重新标注的评估数据集，并设计了针对性的评价指标，用于衡量抽取结果与UOC语义的一致性。最后，我们利用最先进的生成模型建立了UOCE任务的基线性能。
原文摘要 · Abstract (English)
This paper introduces the Unified Opinion Concepts (UOC) ontology to integrate opinions within their semantic context. The UOC ontology bridges the gap between the semantic representation of opinion across different formulations. It is a unified conceptualisation based on the facets of opinions studied extensively in NLP and semantic structures described through symbolic descriptions. We further propose the Unified Opinion Concept Extraction (UOCE) task of extracting opinions from the text with enhanced expressivity. Additionally, we provide a manually extended and re-annotated evaluation dataset for this task and tailored evaluation metrics to assess the adherence of extracted opinions to UOC semantics. Finally, we establish baseline performance for the UOCE task using state-of-the-art generative models.
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