ABBE语料库：有情感的生物
The ABBE Corpus: Animate Beings Being Emotional
摘要：
情感检测是一项已建立的NLP任务，已被证明可用于文本理解。然而，基本的情绪检测遗漏了关键信息，即谁正在经历所讨论的情绪。例如，它可能是作者，叙述者或角色;或者情感可能对应于观众应该感受到的东西，甚至无法归因于特定的存在，例如，当我们讨论情感的时候我们提供了阿贝语料库-动画的存在是情感-一个新的双注释语料库的文本，捕捉这类情感体验者的关键信息，即，动画的存在，在世界上所描述的文本。这样的语料库对于开发试图建模或理解这种特定类型的表达情感的系统是有用的。我们的语料库包含30个章节，134，513个单词，来自英语小说语料库，包含2，010个独特的情感表达，可归因于2，227个生物。根据Plutchik的8类情感模型对情感表达进行分类，注释的整体注释者间一致性为0.83 Cohen Kappa，表明非常一致。我们详细描述了我们的注释方案和过程，并发布语料库供其他研究人员使用。
英文摘要：
Emotion detection is an established NLP task of demonstrated utility for text understanding. However, basic emotion detection leaves out key information, namely, who is experiencing the emotion in question. For example, it may be the author, the narrator, or a character; or the emotion may correspond to something the audience is supposed to feel, or even be unattributable to a specific being, e.g., when emotions are being discussed per se. We provide the ABBE corpus -- Animate Beings Being Emotional -- a new double-annotated corpus of texts that captures this key information for one class of emotion experiencer, namely, animate beings in the world described by the text. Such a corpus is useful for developing systems that seek to model or understand this specific type of expressed emotion. Our corpus contains 30 chapters, comprising 134,513 words, drawn from the Corpus of English Novels, and contains 2,010 unique emotion expressions attributable to 2,227 animate beings. The emotion expressions are categorized according to Plutchik's 8-category emotion model, and the overall inter-annotator agreement for the annotations was 0.83 Cohen's Kappa, indicating excellent agreement. We describe in detail our annotation scheme and procedure, and also release the corpus for use by other researchers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
