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}
翻译:在本文中,我们关注通常被忽视的问题,即: \ textit{ 相似性应该从不同角度确定}。为了探讨这一问题,我们发布了多视角文本相似性数据集,其中从12个角度标出了句相似性标签。此外,我们通过修改一些著名的文本匹配模型,对这项任务进行一系列实验性分析。最后,我们获得了若干结论和基线模型,为对这一问题的以下调查奠定了基础。数据集和代码可在Github\ footoot@url{https://github.com/autooliuweijie/MPTS}公开查阅。