QALD-9-Plus Dataset for Knowledge Graph Question Answering
License: Creative Commons Attribution 4.0 International
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qald_9_plus's Introduction
QALD-9-plus Dataset Description
QALD-9-plus is the dataset for Knowledge Graph Question Answering (KGQA) based on well-known QALD-9.
QALD-9-plus enables to train and test KGQA systems over DBpedia and Wikidata using questions in 9 different languages: English, German, Russian, French, Armenian, Belarusian, Lithuanian, Bashkir, and Ukrainian.
Some of the questions have several alternative writings in particular languages which enables to evaluate the robustness of KGQA systems and train paraphrasing models.
As the questions' translations were provided by native speakers, they are considered as "gold standard", therefore, machine translation tools can be trained and evaluated on the dataset.
Dataset Statistics
en
de
fr
ru
uk
lt
be
ba
hy
# questions DBpedia
# questions Wikidata
Train
408
543
260
1203
447
468
441
284
80
408
371
Test
150
176
26
348
176
186
155
117
20
150
136
Given the numbers, it is obvious that some of the languages are covered more than once i.e., there is more than one translation for a particular question.
For example, there are 1203 Russian translations available while only 408 unique questions exist in the training subset (i.e., 2.9 Russian translations per one question).
The availability of such parallel corpora enables the researchers, developers and other dataset users to address the paraphrasing task.
Evaluation
We used GERBIL system for the evaluation of the dataset. The detailed information for the experiments is available at the individual link (click the value in the cells).
@inproceedings{perevalov2022qald9plus,
author={Perevalov, Aleksandr and Diefenbach, Dennis and Usbeck, Ricardo and Both, Andreas},
booktitle={2022 IEEE 16th International Conference on Semantic Computing (ICSC)},
title={QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers},
year={2022},
pages={229-234},
doi={10.1109/ICSC52841.2022.00045}
}
QALD-9-Plus is the dataset for Knowledge Graph Question Answering (KGQA) based on well-known QALD-9.
QALD-9-Plus enables to train and test KGQA systems over DBpedia and Wikidata using questions in 9 different languages: English, German, Russian, French, Armenian, Belarusian, Lithuanian, Bashkir, and Ukrainian.
Some of the questions have several alternative writings in particular languages which enables to evaluate the robustness of KGQA systems and train paraphrasing models.
As the questions' translations were provided by native speakers, they are considered as "gold standard", therefore, machine translation tools can be trained and evaluated on the dataset.
license
property
value
name
CC-BY-4.0
url
https://creativecommons.org/licenses/by/4.0/
citation
Perevalov, Aleksandr, Diefenbach, Diefenback, Usbeck, Ricardo, Both, Andreas: QALD-9-plus: A multilingual dataset for question answering over DBpedia and Wikidata translated by native speakers. In: 2022 IEEE 16th International Conference on Semantic Computing (ICSC). IEEE (2022)