CEREC

CEREC是由德克萨斯大学达拉斯分校计算机科学系创建的第一个大规模电子邮件对话实体解析语料库。该数据集包含6001个来自Enron电子邮件语料库的电子邮件线程，总计36,448封电子邮件和60,383个实体共指链。数据集的标注过程分为两个步骤，尽量减少人工干预。CEREC主要用于评估不同的特征和四个基线模型在创建的语料库上的性能，旨在解决电子邮件对话中的实体解析问题。

CEREC is the first large-scale email conversation entity resolution corpus created by the Department of Computer Science at the University of Texas at Dallas. This dataset contains 6,001 email threads sourced from the Enron Email Corpus, totaling 36,448 emails and 60,383 entity coreference chains. The annotation process of the dataset is divided into two steps to minimize manual intervention. CEREC is primarily used to evaluate the performance of different features and four baseline models on the constructed corpus, aiming to solve the entity resolution problem in email conversations.