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qald_9_plus

QALD-9-Plus Dataset for Knowledge Graph Question Answering

https://github.com/kgqa/qald_9_plus

Science Score: 67.0%

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Repository

QALD-9-Plus Dataset for Knowledge Graph Question Answering

Basic Info
  • Host: GitHub
  • Owner: KGQA
  • License: cc-by-4.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 4.01 MB
Statistics
  • Stars: 27
  • Watchers: 4
  • Forks: 7
  • Open Issues: 6
  • Releases: 0
Created over 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

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

bibtex @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)

Owner

  • Name: Knowledge Graph Question Answering
  • Login: KGQA
  • Kind: organization

A collaboration between HTWK Leipzig, HS Anhalt, FhG IAIS and Semantic Systems @ University Hamburg

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  QALD-9-plus: A Multilingual Dataset for Question
  Answering over DBpedia and Wikidata Translated by
  Native Speakers
message: >-
  If you use this dataset, please cite it using the
  metadata from this file.
type: dataset
authors:
  - given-names: Aleksandr
    family-names: Perevalov
    email: perevalovproduction@gmail.com
    affiliation: Anhalt University of Applied Sciences
    orcid: 'https://orcid.org/0000-0002-6803-3357'
  - given-names: Dennis
    family-names: Diefenbach
    email: dennis.diefenbach@univ-st-etienne.fr
    affiliation: >-
      Laboratoire Hubert Curien CNRS UMR 5516
      Université de Lyon
    orcid: 'https://orcid.org/0000-0002-0046-2219'
  - given-names: Ricardo
    family-names: Usbeck
    email: ricardo.usbeck@uni-hamburg.de
    affiliation: Universität Hamburg
    orcid: 'https://orcid.org/0000-0002-0191-7211'
  - given-names: Andreas
    family-names: Both
    email: andreas.both@hs-anhalt.de
    affiliation: Anhalt University of Applied Sciences
    orcid: 'https://orcid.org/0000-0002-9177-5463'

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