Temporal Twitter Corpus

It includes 12,000 tweets annotated for the named entity recognition task. The tweets are uniformly distributed over the years 2014-2019, with 2,000 tweets from each year. The goal is to have a temporally diverse corpus to account for data drift over time when building NER models.

搜集汇总

背景与挑战

背景概述

该数据集包含12,000条推文，专门用于命名实体识别任务，推文均匀覆盖2014至2019年，每年2000条，旨在构建一个时间多样化的语料库以应对数据漂移。实体标注类型包括位置、人物和组织，数据以JSON格式提供。