No One is Perfect: Analysing the Performance of Question Answering Components over the DBpedia Knowledge Graph

TL;DR

This paper evaluates 29 question answering components over the DBpedia knowledge graph, identifying common failure modes and suggesting future research directions to improve QA system performance.

Contribution

It provides a comprehensive micro evaluation of existing QA components for DBpedia, highlighting their weaknesses and proposing characteristics for better future designs.

Findings

Identification of common failure cases among QA components

Analysis of characteristics hindering QA performance

Future challenges and research directions outlined

Abstract

Question answering (QA) over knowledge graphs has gained significant momentum over the past five years due to the increasing availability of large knowledge graphs and the rising importance of question answering for user interaction. DBpedia has been the most prominently used knowledge graph in this setting and most approaches currently use a pipeline of processing steps connecting a sequence of components. In this article, we analyse and micro evaluate the behaviour of 29 available QA components for DBpedia knowledge graph that were released by the research community since 2010. As a result, we provide a perspective on collective failure cases, suggest characteristics of QA components that prevent them from performing better and provide future challenges and research directions for the field.