QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers

TL;DR

QALD-9-plus is a multilingual dataset extension for KGQA, featuring high-quality translations in 8 languages, including endangered ones, and transferring questions from DBpedia to Wikidata to enhance accessibility and usability.

Contribution

The paper introduces QALD-9-plus, a novel multilingual KGQA benchmark with native speaker translations in 8 languages and transfer to Wikidata, addressing accessibility challenges.

Findings

Includes translations in 8 languages, 5 of which are new to KGQA research.

Transfers questions from DBpedia to Wikidata, increasing dataset relevance.

Provides high-quality, native speaker translations for improved accessibility.

Abstract

The ability to have the same experience for different user groups (i.e., accessibility) is one of the most important characteristics of Web-based systems. The same is true for Knowledge Graph Question Answering (KGQA) systems that provide the access to Semantic Web data via natural language interface. While following our research agenda on the multilingual aspect of accessibility of KGQA systems, we identified several ongoing challenges. One of them is the lack of multilingual KGQA benchmarks. In this work, we extend one of the most popular KGQA benchmarks - QALD-9 by introducing high-quality questions' translations to 8 languages provided by native speakers, and transferring the SPARQL queries of QALD-9 from DBpedia to Wikidata, s.t., the usability and relevance of the dataset is strongly increased. Five of the languages - Armenian, Ukrainian, Lithuanian, Bashkir and Belarusian - to our best knowledge were never considered in KGQA research community before. The latter two of the languages are considered as "endangered" by UNESCO. We call the extended dataset QALD-9-plus and made it available online https://github.com/Perevalov/qald_9_plus.