Abstract
Simple questions are the most common type of questions used for evaluating a knowledge graph question answering (KGQA). A simple question is a question whose answer can be captured by a factoid statement with one relation or predicate. Knowledge graph question answering (KGQA) systems are systems whose aim is to automatically answer natural language questions (NLQs) over knowledge graphs (KGs). There are varieties of researches with different approaches in this area. However, the lack of a comprehensive study to focus on addressing simple questions from all aspects is tangible. In this paper, we present a comprehensive survey of answering simple questions to classify available techniques and compare their advantages and drawbacks in order to have better insights of existing issues and recommendations to direct future works.
Highlights
Knowledge graph questions answering (KGQA) systems enable users to retrieve data from a knowledge graph (KG) without requiring a complete understanding of the knowledge graphs (KGs) schema
In comparison to the survey conducted by Höffner et al, our survey considered a wider range of publication year, namely from 2010 to 2021, in the end, no system prior to the year 2015 is selected for a more detailed elaboration because we found that there is no specialized benchmark on knowledge graph simple question answering (KGSQA) prior to the SimpleQuestions data set
A KG is as a set K of assertions, each of which is expressed as a triple of the form (s, p, o )
Summary
Knowledge graph questions answering (KGQA) systems enable users to retrieve data from a knowledge graph (KG) without requiring a complete understanding of the KG schema. Instead of formulating a precise query in a particular, formal query language, users can obtain data from a KG by formulating their information need in the form of a natural language question (NLQ) Realizing such a system requires one to address the gap between the input NLQ, which is unstructured, and the desired answer represented by data in the KG, which are in a structured form and possibly specified under a complex schema. Research leading to various solutions to these tasks led to the emergence of KGQA as an exciting research direction This is indicated by the development of a number of KGQA systems in the last several years
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