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.

提供了一个新的英文小说语料库-ABBE corpus，它包含来自134513个单词的30个章节，其中包含了2010个唯一的动物表达的情感表达式，用于模拟和理解表达的情感，并根据Plutchik的8类情感模型对其进行了分类，并且在注释方面具有很高的互评一致性。

ABBE语料库：有情感的动物