Natural Language to SPARQL

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Overview

Natural language to SPARQL studies how to turn questions into queries that retrieve answers from structured knowledge graphs. Systems use language models with schema and ontology context, entity and relation grounding, question decomposition, and retrieved examples; some also refine queries using execution feedback or graph constraints. Methods are evaluated on benchmarks involving Wikidata, Freebase, DBpedia, and domain-specific graphs, with growing attention to execution accuracy, runtime, and cost. A central challenge is grounding ambiguous questions in unfamiliar or changing schemas, while exact query matching can fail to reflect whether a system returns the right answer.

Latest papers

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15 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

  1. Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing

    Oct 6, 2026Remo Grillo, Lukas Klic, Giovanni ColavizzaLLM GroundingKnowledge Graphs

    University of Bologna, Via Zamboni 33, 40126 Bologna, Italy · I Tatti — The Harvard University Center for Italian Renaissance Studies, Via di Vincigliata 26, 50135 Florence, Italy · Department of Communication, University of Copenhagen, Karen Blixens Plads 8, 2300 Copenhagen S, Denmark

  2. Build2SPARQL: A Large-Scale Text-to-SPARQL Benchmark Dataset for Building Knowledge Graph Querying

    Sep 22, 2026Wooyoung JungBenchmark ConstructionNatural Language to SPARQL

    Assistant Professor, Dept. of Civil and Architectural Engineering and Mechanics, Univ. of Arizona, Tucson, AZ 85719.

  3. Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Window

    Sep 13, 2026Blake G. FitchKnowledge Graph Question AnsweringNatural Language to SPARQL

    Max Planck Institute for Biological Cybernetics, Tübingen, Germany

  4. Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)

    Sep 10, 2026Harshdeep Singh, Yurui Zhu, Giovanni Colavizza +1Graph Retrieval-Augmented GenerationKnowledge Graph Question Answering

    Odoma Ltd.

  5. AutoSchema: Live Schema Grounding for Agentic Text-to-Sparql over Heterogeneous Knowledge Graphs

    Aug 14, 2026Yiming Zhang, Koji TsudaNatural Language to SPARQLSchema Linking

    The University of Tokyo Kashiwa, Chiba, Japan · Center for Basic Research on Materials, National Institute for Materials Science Tsukuba, Ibaraki, Japan · RIKEN Center for Advanced Intelligence Project Tokyo, Japan

  6. Towards Researcher Agents for Knowledge-Graph Question Answering

    Aug 7, 2026Tommaso Soru, Abdulsobur OyewaleLLM Agent Self-ImprovementKnowledge Graph Question Answering

    1Liber AI Research, London, United Kingdom

  7. GGC: Selective Query Correction for Reliable Text-to-SPARQL Generation

    Jul 30, 2026Ziyi Yang, Thanh-Son Nguyen, Tuan Anh Nguyen +1LLM Self-CorrectionLLM Reliability

    1Nanyang Technological University, Centre for Info. Sciences and Systems · Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore

  8. Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation

    Jul 20, 2026Blake G. Fitch, Cato Elia KurtzKnowledge RepresentationKnowledge Graph Question Answering

    Max Planck Institute for Biological Cybernetics Tübingen, Germany

  9. SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation

    Jul 16, 2026Yiming Zhang, Koji TsudaLLM GroundingKnowledge Graph Question Answering

    1The University of Tokyo, Japan · Center for Basic Research on Materials, National Institute for Materials Science, Japan · 3RIKEN Center for Advanced Intelligence Project, Japan

  10. DeSQ: Decomposition-based SPARQL Query Generation

    May 29, 2026Papa Abdou Karim Karou Diallo, Aditya Sharma, Neshat Elhami Fard +1Question DecompositionEntity Linking

    LAMA-WeST · Mila – Quebec AI Institute · Polytechnique Montréal

  11. mcp-proto-okn: Natural-language access to open scientific knowledge graphs through the Model Context Protocol

    May 28, 2026Peter W. Rose, Benjamin M. Good, Amanda M. Saravia-Butler +7Knowledge Graph Question AnsweringKnowledge Graphs

    San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA · The Scripps Research Institute, La Jolla, CA 92037, USA · Amentum, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA 94035, USA +3

  12. Text-to-SPARQL Generation with Reinforcement Learning: A GRPO-based Approach on DBLP

    May 19, 2026Jann Pfeifer, Debayan Banerjee, Ricardo UsbeckRL for Language ModelsKnowledge Graph Question Answering

    Leuphana University Lüneburg, Germany

  13. GRISP: Guided Recurrent IRI Selection over SPARQL Skeletons

    Apr 22, 2026Sebastian Walter, Hannah BastKnowledge Graph Question AnsweringKnowledge Graphs

    University of Freiburg · Department of Computer Science · Freiburg im Breisgau, Germany

  14. The Wikidata Query Logs Dataset

    Feb 16, 2026Sebastian Walter, Hannah BastKnowledge Graph Question AnsweringKnowledge Graphs

    University of Freiburg, Department of Computer Science, Freiburg im Breisgau, Germany

  15. SPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions

    Dec 16, 2025Panayiotis Smeros, Vincent Emonet, Ruijie Wang +2Knowledge Graph Question AnsweringNatural Language to SPARQL

    SIB Swiss Institute of Bioinformatics, Switzerland · SIB Swiss Institute of Bioinformatics and University of Zurich, Switzerland