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QALD-9-Plus Dataset for Knowledge Graph Question Answering

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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 10 different languages: English, German, Russian, French, Spanish, 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 es # questions DBpedia # questions Wikidata
Train 408 543 260 1203 447 468 441 284 80 408 408 371
Test 150 176 26 348 176 186 155 117 20 150 150 136

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 the GERBIL QA 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).

Wikidata

QAnswer

en de ru fr es
Test link link link link link
Train link link link link link

DeepPavlov

en ru
Test link link
Train link link

Platypus

en fr
Test link link
Train link link

DBpedia

QAnswer

en de ru fr
Test link link link link
Train link link link link

Wikidata Original Translations

QAnswer

de ru fr
Test link link link
Train link link link

DeepPavlov

ru
Test link
Train link

Platypus

fr
Test link
Train link

DBpedia Original Translations

QAnswer

de ru fr
Test link link link
Train link link link

Cite

@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}
}

Useful Links

Licence CC BY 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License.

CC BY 4.0

Dataset Metadata

The following table is necessary for this dataset to be indexed by search engines such as Google Dataset Search.

property value
name QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers
alternateName QALD-9-plus
url
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.
license
property value
name CC-BY-4.0
url
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)

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