Emotions are a subject of intense debate in various disciplines. Despite the proliferation of theories and definitions, there is still no consensus on what emotions are, and how to model the different concepts involved when we talk about - or categorize - them. In this paper, we propose an OWL frame-based ontology of emotions: the Emotion Frames Ontology (EFO). EFO treats emotions as semantic frames, with a set of semantic roles that capture the different aspects of emotional experience. EFO follows pattern-based ontology design, and is aligned to the DOLCE foundational ontology. EFO is used to model multiple emotion theories, which can be cross-linked as modules in an Emotion Ontology Network. In this paper, we exemplify it by modeling Ekman's Basic Emotions (BE) Theory as an EFO-BE module, and demonstrate how to perform automated inferences on the representation of emotion situations. EFO-BE has been evaluated by lexicalizing the BE emotion frames from within the Framester knowledge graph, and implementing a graph-based emotion detector from text. In addition, an EFO integration of multimodal datasets, including emotional speech and emotional face expressions, has been performed to enable further inquiry into crossmodal emotion semantics.

翻译：情感在不同学科中是激烈争论的主题。尽管存在众多理论和定义，但关于情感的本质以及如何建模谈及或分类情感时所涉及的不同概念，尚未达成共识。本文提出了一种基于OWL框架的情感本体论：情感框架本体（EFO）。EFO将情感视为语义框架，通过一组语义角色捕捉情感体验的不同方面。EFO遵循基于模式的本体设计，并与DOLCE基础本体论对齐。EFO用于建模多种情感理论，这些理论可作为模块相互链接，形成情感本体网络。本文以建模埃克曼基本情感理论为例，构建了EFO-BE模块，并展示了如何在情感情境表征上执行自动推理。EFO-BE通过从Framester知识图谱中词汇化基本情感框架、实现基于图的情感文本检测器进行了评估。此外，EFO还集成了包括情感语音和面部表情在内的多模态数据集，以支持跨模态情感语义的进一步探索。