  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.

Computation and Language;Information Retrieval