Related papers: Temporal Knowledge Graph Question Answering: A Survey

Temporal Knowledge Graph Question Answering: A Survey

URL: http://arxiv.org/abs/2406.14191v2
Date: Fri, 5 Jul 2024 07:38:02 GMT
Title: Temporal Knowledge Graph Question Answering: A Survey
Authors: Miao Su, Zixuan Li, Zhuo Chen, Long Bai, Xiaolong Jin, Jiafeng Guo,
Abstract summary: Temporal Knowledge Graph Question Answering (TKGQA) is an emerging task to answer temporal questions. This paper provides a thorough survey from two perspectives: the taxonomy of temporal questions and the methodological categorization for TKGQA.
Score: 39.40384139630724
License: http://creativecommons.org/licenses/by/4.0/
Abstract: 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.

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