A Comparative Evaluation of Visual and Natural Language Question Answering over Linked Data

Gerhard Wohlgenannt, Dmitry Mouromtsev, Dmitry Pavlov, Yury Emelyanov, Alexey Morozov

2019

Abstract

With the growing number and size of Linked Data datasets, it is crucial to make the data accessible and useful for users without knowledge of formal query languages. Two approaches towards this goal are knowledge graph visualization and natural language interfaces. Here, we investigate specifically question answering (QA) over Linked Data by comparing a diagrammatic visual approach with existing natural language-based systems. Given a QA benchmark (QALD7), we evaluate a visual method which is based on iteratively creating diagrams until the answer is found, against four QA systems that have natural language queries as input. Besides other benefits, the visual approach provides higher performance, but also requires more manual input. The results indicate that the methods can be used complementary, and that such a combination has a large positive impact on QA performance, and also facilitates additional features such as data exploration.

Paper Citation

in Harvard Style

Wohlgenannt G., Mouromtsev D., Pavlov D., Emelyanov Y. and Morozov A. (2019). A Comparative Evaluation of Visual and Natural Language Question Answering over Linked Data. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD; ISBN 978-989-758-382-7, SciTePress, pages 473-478. DOI: 10.5220/0008364704730478

in Bibtex Style

@conference{keod19,
author={Gerhard Wohlgenannt and Dmitry Mouromtsev and Dmitry Pavlov and Yury Emelyanov and Alexey Morozov},
title={A Comparative Evaluation of Visual and Natural Language Question Answering over Linked Data},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD},
year={2019},
pages={473-478},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008364704730478},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 2: KEOD
TI - A Comparative Evaluation of Visual and Natural Language Question Answering over Linked Data
SN - 978-989-758-382-7
AU - Wohlgenannt G.
AU - Mouromtsev D.
AU - Pavlov D.
AU - Emelyanov Y.
AU - Morozov A.
PY - 2019
SP - 473
EP - 478
DO - 10.5220/0008364704730478
PB - SciTePress