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

arXiv: https://arxiv.org/abs/2202.00120 · HTML: https://mlsanity.com/paper/2202.00120/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 19 references that are in the map.
- First posted on arXiv 31 Jan 2022.

## Builds on (most cited first, 3 of 3)

- [Measuring Compositional Generalization: A Comprehensive Method on Realistic Data](https://mlsanity.com/paper/1912.09713/) (2019)
- [Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering](https://mlsanity.com/paper/1808.04126/) (2018)
- [Towards a Question Answering System over the Semantic Web](https://mlsanity.com/paper/1803.00832/) (2018)

## Built on by (most cited first, 30 of 39)

- [Graph Retrieval-Augmented Generation: A Survey](https://mlsanity.com/paper/2408.08921/) (2024)
- [Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph](https://mlsanity.com/paper/2307.07697/) (2023)
- [Neuro-Symbolic AI in 2024: A Systematic Review](https://mlsanity.com/paper/2501.05435/) (2025)
- [SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questions](https://mlsanity.com/paper/2407.11417/) (2024)
- [Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey](https://mlsanity.com/paper/2504.10499/) (2025)
- [A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applications](https://mlsanity.com/paper/2404.14809/) (2024)
- [An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration](https://mlsanity.com/paper/2402.04978/) (2024)
- [EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs](https://mlsanity.com/paper/2406.01238/) (2024)
- [Leveraging small language models for Text2SPARQL tasks to improve the resilience of AI assistance](https://mlsanity.com/paper/2405.17076/) (2024)
- [Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking](https://mlsanity.com/paper/2505.23495/) (2025)
- [Beyond Static Models and Test Sets: Benchmarking the Potential of Pre-trained Models Across Tasks and Languages](https://mlsanity.com/paper/2205.06356/) (2022)
- [Reliable Reasoning Path: Distilling Effective Guidance for LLM Reasoning with Knowledge Graphs](https://mlsanity.com/paper/2506.10508/) (2025)
- [Enhancing Large Language Models with Pseudo- and Multisource- Knowledge Graphs for Open-ended Question Answering](https://mlsanity.com/paper/2402.09911/) (2024)
- [ODA: Observation-Driven Agent for integrating LLMs and Knowledge Graphs](https://mlsanity.com/paper/2404.07677/) (2024)
- [Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine Translation](https://mlsanity.com/paper/2503.06594/) (2025)
- [Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions](https://mlsanity.com/paper/2212.10189/) (2022)
- [Towards Automatic Composition of ASP Programs from Natural Language Specifications](https://mlsanity.com/paper/2403.04541/) (2024)
- [Enrich-on-Graph: Query-Graph Alignment for Complex Reasoning with LLM Enriching](https://mlsanity.com/paper/2509.20810/) (2025)
- [SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection](https://mlsanity.com/paper/2507.13859/) (2025)
- [MST5 -- Multilingual Question Answering over Knowledge Graphs](https://mlsanity.com/paper/2407.06041/) (2024)
- [FIRESPARQL: A LLM-based Framework for SPARQL Query Generation over Scholarly Knowledge Graphs](https://mlsanity.com/paper/2508.10467/) (2025)
- [Search-on-Graph: Iterative Informed Navigation for Large Language Model Reasoning on Knowledge Graphs](https://mlsanity.com/paper/2510.08825/) (2025)
- [MASSIVE Multilingual Abstract Meaning Representation: A Dataset and Baselines for Hallucination Detection](https://mlsanity.com/paper/2405.19285/) (2024)
- [Last Layer Logits to Logic: Empowering LLMs with Logic-Consistent Structured Knowledge Reasoning](https://mlsanity.com/paper/2511.07910/) (2025)
- [Data Distribution Bottlenecks in Grounding Language Models to Knowledge Bases](https://mlsanity.com/paper/2309.08345/) (2023)
- [SPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions](https://mlsanity.com/paper/2512.14277/) (2025)
- [GraphextQA: A Benchmark for Evaluating Graph-Enhanced Large Language Models](https://mlsanity.com/paper/2310.08487/) (2023)
- [Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction](https://mlsanity.com/paper/2408.02337/) (2024)
- [Protoknowledge Shapes Behaviour of LLMs in Downstream Tasks: Memorization and Generalization with Knowledge Graphs](https://mlsanity.com/paper/2505.15501/) (2025)
- [Automating SPARQL Query Translations between DBpedia and Wikidata](https://mlsanity.com/paper/2507.10045/) (2025)

## Abstract (arXiv)

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.