---
_id: '57240'
abstract:
- lang: eng
text: Validating assertions before adding them to a knowledge graph is an essential
part of its creation and maintenance. Due to the sheer size of knowledge graphs,
automatic fact-checking approaches have been developed. These approaches rely
on reference knowledge to decide whether a given assertion is correct. Recent
hybrid approaches achieve good results by including several knowledge sources.
However, it is often impractical to provide a sheer quantity of textual knowledge
or generate embedding models to leverage these hybrid approaches. We present FaVEL,
an approach that uses algorithm selection and ensemble learning to amalgamate
several existing fact-checking approaches that rely solely on a reference knowledge
graph and, hence, use fewer resources than current hybrid approaches. For our
evaluation, we create updated versions of two existing datasets and a new dataset
dubbed FaVEL-DS. Our evaluation compares our approach to 15 fact-checking approaches—including
the state-of-the-art approach HybridFC—on 3 datasets. Our results demonstrate
that FaVEL outperforms all other approaches significantly by at least 0.04 in
terms of the area under the ROC curve. Our source code, datasets, and evaluation
results are open-source and can be found at https://github.com/dice-group/favel.
author:
- first_name: Umair
full_name: Qudus, Umair
id: '83392'
last_name: Qudus
orcid: 0000-0001-6714-8729
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Franck Lionel
full_name: Tatkeu Pekarou, Franck Lionel
last_name: Tatkeu Pekarou
- first_name: Ana Alexandra
full_name: Morim da Silva, Ana Alexandra
id: '72108'
last_name: Morim da Silva
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Qudus U, Röder M, Tatkeu Pekarou FL, Morim da Silva AA, Ngonga Ngomo A-C.
FaVEL: Fact Validation Ensemble Learning. In: Rospocher M, Mehwish Alam, eds.
EKAW 2024. ; 2024.'
apa: 'Qudus, U., Röder, M., Tatkeu Pekarou, F. L., Morim da Silva, A. A., &
Ngonga Ngomo, A.-C. (2024). FaVEL: Fact Validation Ensemble Learning. In M. Rospocher
& Mehwish Alam (Eds.), EKAW 2024.'
bibtex: '@inproceedings{Qudus_Röder_Tatkeu Pekarou_Morim da Silva_Ngonga Ngomo_2024,
title={FaVEL: Fact Validation Ensemble Learning}, booktitle={EKAW 2024}, author={Qudus,
Umair and Röder, Michael and Tatkeu Pekarou, Franck Lionel and Morim da Silva,
Ana Alexandra and Ngonga Ngomo, Axel-Cyrille}, editor={Rospocher, Marco and Mehwish
Alam}, year={2024} }'
chicago: 'Qudus, Umair, Michael Röder, Franck Lionel Tatkeu Pekarou, Ana Alexandra
Morim da Silva, and Axel-Cyrille Ngonga Ngomo. “FaVEL: Fact Validation Ensemble
Learning.” In EKAW 2024, edited by Marco Rospocher and Mehwish Alam, 2024.'
ieee: 'U. Qudus, M. Röder, F. L. Tatkeu Pekarou, A. A. Morim da Silva, and A.-C.
Ngonga Ngomo, “FaVEL: Fact Validation Ensemble Learning,” in EKAW 2024,
Amsterdam, Netherlands, 2024.'
mla: 'Qudus, Umair, et al. “FaVEL: Fact Validation Ensemble Learning.” EKAW 2024,
edited by Marco Rospocher and Mehwish Alam, 2024.'
short: 'U. Qudus, M. Röder, F.L. Tatkeu Pekarou, A.A. Morim da Silva, A.-C. Ngonga
Ngomo, in: M. Rospocher, Mehwish Alam (Eds.), EKAW 2024, 2024.'
conference:
end_date: 2024-11-28
location: Amsterdam, Netherlands
name: 24th International Conference on Knowledge Engineering and Knowledge Management
start_date: 2024-11-26
corporate_editor:
- Mehwish Alam
date_created: 2024-11-19T14:12:49Z
date_updated: 2025-09-11T09:48:12Z
ddc:
- '600'
department:
- _id: '34'
editor:
- first_name: Marco
full_name: Rospocher, Marco
last_name: Rospocher
file:
- access_level: closed
content_type: application/pdf
creator: uqudus
date_created: 2024-11-19T14:14:14Z
date_updated: 2024-11-19T14:14:14Z
file_id: '57241'
file_name: favel.pdf
file_size: 190661
relation: main_file
success: 1
file_date_updated: 2024-11-19T14:14:14Z
has_accepted_license: '1'
keyword:
- fact checking
- ensemble learning
- transfer learning
- knowledge management.
language:
- iso: eng
popular_science: '1'
project:
- _id: '412'
name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen'
- _id: '285'
name: 'SAIL: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen
Systemen'
- _id: '410'
name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale'
publication: EKAW 2024
quality_controlled: '1'
status: public
title: 'FaVEL: Fact Validation Ensemble Learning'
type: conference
user_id: '83392'
year: '2024'
...
---
_id: '57278'
author:
- first_name: Ana Alexandra
full_name: Morim da Silva, Ana Alexandra
id: '72108'
last_name: Morim da Silva
- first_name: Nikit
full_name: Srivastava, Nikit
id: '70066'
last_name: Srivastava
orcid: 0009-0004-5164-4911
- first_name: Tatiana
full_name: Moteu Ngoli, Tatiana
id: '99174'
last_name: Moteu Ngoli
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Morim da Silva AA, Srivastava N, Moteu Ngoli T, Röder M, Moussallem D, Ngonga
Ngomo A-C. Benchmarking Low-Resource Machine Translation Systems. In: Proceedings
of the Seventh Workshop on Technologies for Machine Translation of Low-Resource
Languages (LoResMT 2024). Association for Computational Linguistics; 2024.
doi:10.18653/v1/2024.loresmt-1.18'
apa: Morim da Silva, A. A., Srivastava, N., Moteu Ngoli, T., Röder, M., Moussallem,
D., & Ngonga Ngomo, A.-C. (2024). Benchmarking Low-Resource Machine Translation
Systems. Proceedings of the Seventh Workshop on Technologies for Machine Translation
of Low-Resource Languages (LoResMT 2024). https://doi.org/10.18653/v1/2024.loresmt-1.18
bibtex: '@inproceedings{Morim da Silva_Srivastava_Moteu Ngoli_Röder_Moussallem_Ngonga
Ngomo_2024, title={Benchmarking Low-Resource Machine Translation Systems}, DOI={10.18653/v1/2024.loresmt-1.18},
booktitle={Proceedings of the Seventh Workshop on Technologies for Machine Translation
of Low-Resource Languages (LoResMT 2024)}, publisher={Association for Computational
Linguistics}, author={Morim da Silva, Ana Alexandra and Srivastava, Nikit and
Moteu Ngoli, Tatiana and Röder, Michael and Moussallem, Diego and Ngonga Ngomo,
Axel-Cyrille}, year={2024} }'
chicago: Morim da Silva, Ana Alexandra, Nikit Srivastava, Tatiana Moteu Ngoli, Michael
Röder, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “Benchmarking Low-Resource
Machine Translation Systems.” In Proceedings of the Seventh Workshop on Technologies
for Machine Translation of Low-Resource Languages (LoResMT 2024). Association
for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.loresmt-1.18.
ieee: 'A. A. Morim da Silva, N. Srivastava, T. Moteu Ngoli, M. Röder, D. Moussallem,
and A.-C. Ngonga Ngomo, “Benchmarking Low-Resource Machine Translation Systems,”
2024, doi: 10.18653/v1/2024.loresmt-1.18.'
mla: Morim da Silva, Ana Alexandra, et al. “Benchmarking Low-Resource Machine Translation
Systems.” Proceedings of the Seventh Workshop on Technologies for Machine Translation
of Low-Resource Languages (LoResMT 2024), Association for Computational Linguistics,
2024, doi:10.18653/v1/2024.loresmt-1.18.
short: 'A.A. Morim da Silva, N. Srivastava, T. Moteu Ngoli, M. Röder, D. Moussallem,
A.-C. Ngonga Ngomo, in: Proceedings of the Seventh Workshop on Technologies for
Machine Translation of Low-Resource Languages (LoResMT 2024), Association for
Computational Linguistics, 2024.'
date_created: 2024-11-20T10:41:16Z
date_updated: 2025-12-02T19:29:53Z
doi: 10.18653/v1/2024.loresmt-1.18
language:
- iso: eng
publication: Proceedings of the Seventh Workshop on Technologies for Machine Translation
of Low-Resource Languages (LoResMT 2024)
publication_status: published
publisher: Association for Computational Linguistics
status: public
title: Benchmarking Low-Resource Machine Translation Systems
type: conference
user_id: '70066'
year: '2024'
...