Knowledge Base Question Answering (KBQA) has been a long-standing field to
answer questions based on knowledge bases. Recently, the evolving dynamics of
knowledge have attracted a growing interest in Temporal Knowledge Graph
Question Answering (TKGQA), an emerging task to answer temporal questions.
However, this field grapples with ambiguities in defining temporal questions
and lacks a systematic categorization of existing methods for TKGQA. In
response, this paper provides a thorough survey from two perspectives: the
taxonomy of temporal questions and the methodological categorization for TKGQA.
Specifically, we first establish a detailed taxonomy of temporal questions
engaged in prior studies. Subsequently, we provide a comprehensive review of
TKGQA techniques of two categories: semantic parsing-based and TKG
embedding-based. Building on this review, the paper outlines potential research
directions aimed at advancing the field of TKGQA. This work aims to serve as a
comprehensive reference for TKGQA and to stimulate further research.

本文从两个角度，即时间问题的分类和基于语义解析和知识图嵌入的方法论分类，对时间知识图问答（TKGQA）进行了全面概述，为该领域的发展提供了参考，并激发了进一步研究的动力。