In this paper, we pay attention to the issue which is usually overlooked, i.e., \textit{similarity should be determined from different perspectives}. To explore this issue, we release a Multi-Perspective Text Similarity (MPTS) dataset, in which sentence similarities are labeled from twelve perspectives. Furthermore, we conduct a series of experimental analysis on this task by retrofitting some famous text matching models. Finally, we obtain several conclusions and baseline models, laying the foundation for the following investigation of this issue. The dataset and code are publicly available at Github\footnote{\url{https://github.com/autoliuweijie/MPTS}
@article{arxiv.2202.06517,
title = {Semantic Matching from Different Perspectives},
author = {Weijie Liu and Tao Zhu and Weiquan Mao and Zhe Zhao and Weigang Guo and Xuefeng Yang and Qi Ju},
journal= {arXiv preprint arXiv:2202.06517},
year = {2022}
}