bangzhao/express-emotion-recognition

EXPRESS（EXperiences和PRocessed Emotions in Self-disclosure Stories）是一个用于评估语言模型中细粒度情感识别的基准数据集。它包含33,679条基于Reddit的自然人类经历，每条经历都配有自我披露的情感标签。EXPRESS使用原作者明确披露的情感作为真实标签，涵盖251个细粒度情感标签，平均上下文长度为259个单词，能够评估模型从丰富的现实世界上下文中推断细微情感状态的能力。每个实例在原始文本中使用`<mask>`标记屏蔽自我披露的情感词或短语。

EXPRESS (EXperiences and PRocessed Emotions in Self-disclosure Stories) is a benchmark dataset for evaluating fine-grained emotion recognition in language models. It contains 33,679 naturally occurring Reddit-based human experiences paired with self-disclosed emotion labels. EXPRESS uses emotions explicitly disclosed by the original authors as ground-truth labels. The dataset covers 251 fine-grained emotion labels and an average context length of 259 words, enabling evaluation of models’ ability to infer nuanced emotional states from rich real-world contexts. Each instance masks the self-disclosed emotion word or phrase in the original text using a `<mask>` token.