Knowledge Graph Question Answering Using Graph-Pattern Isomorphism
Abstract: Knowledge Graph Question Answering (KGQA) systems are often based on machine learning algorithms, requiring thousands of question-answer pairs as training examples or natural language processing pipelines that need module fine-tuning. In this paper, we present a novel QA approach, dubbed TeBaQA. Our approach learns to answer questions based on graph isomorphisms from basic graph patterns of SPARQL queries. Learning basic graph patterns is efficient due to the small number of possible patterns. This novel paradigm reduces the amount of training data necessary to achieve state-of-the-art performance. TeBaQA also speeds up the domain adaption process by transforming the QA system development task into a much smaller and easier data compilation task. In our evaluation, TeBaQA achieves state-of-the-art performance on QALD-8 and delivers comparable results on QALD-9 and LC-QuAD v1. Additionally, we performed a fine-grained evaluation on complex queries that deal with aggregation and superlative questions as well as an ablation study, highlighting future research challenges.
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@inproceedings{DBLP:conf/i-semantics/VollmersJMTNU21,
author = {Daniel Vollmers and
Rricha Jalota and
Diego Moussallem and
Hardik Topiwala and
Axel{-}Cyrille Ngonga Ngomo and
Ricardo Usbeck},
editor = {Mehwish Alam and
Paul Groth and
Victor de Boer and
Tassilo Pellegrini and
Harshvardhan J. Pandit and
Elena Montiel{-}Ponsoda and
V{\'{\i}}ctor Rodr{\'{\i}}guez{-}Doncel and
Barbara McGillivray and
Albert Mero{\~{n}}o{-}Pe{\~{n}}uela},
title = {Knowledge Graph Question Answering Using Graph-Pattern Isomorphism},
booktitle = {Further with Knowledge Graphs - Proceedings of the 17th International
Conference on Semantic Systems, SEMANTiCS 2017, Amsterdam, The Netherlands,
September 6-9, 2021},
series = {Studies on the Semantic Web},
volume = {53},
pages = {103--117},
publisher = {{IOS} Press},
year = {2021},
url = {https://doi.org/10.3233/SSW210038},
doi = {10.3233/SSW210038},
timestamp = {Tue, 14 Oct 2025 19:35:48 +0200},
biburl = {https://dblp.org/rec/conf/i-semantics/VollmersJMTNU21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}