Naturally-Occurring Presuppositions in English (NOPE) Corpus

NOPE数据集是由纽约大学语言学系与数据科学中心创建，专注于英语中自然发生的预设现象。该数据集包含1279条记录，涵盖10种不同的预设触发类型，旨在研究预设的上下文敏感性和评估机器学习模型对人类推理的预测能力。数据集通过分析当代美国英语语料库（COCA）中的句子提取，确保了预设触发器的自然性和多样性。NOPE数据集的应用领域包括自然语言理解，特别是预设处理的复杂性和机器学习模型在此领域的性能评估。

The NOPE Dataset was developed by the Department of Linguistics and the Center for Data Science at New York University, focusing on naturally occurring presupposition phenomena in English. It contains 1,279 records covering 10 distinct types of presupposition triggers, aiming to investigate the contextual sensitivity of presuppositions and evaluate the predictive capability of machine learning models for human reasoning. The dataset is extracted from sentences in the Corpus of Contemporary American English (COCA), which ensures the naturalness and diversity of presupposition triggers. Its application fields include natural language understanding, especially the complexity of presupposition processing and the performance evaluation of machine learning models in this domain.