{"ID":2893804,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.11954","arxiv_id":"2507.11954","title":"The benefits of query-based KGQA systems for complex and temporal questions in LLM era","abstract":"Large language models excel in question-answering (QA) yet still struggle with multi-hop reasoning and temporal questions. Query-based knowledge graph QA (KGQA) offers a modular alternative by generating executable queries instead of direct answers. We explore multi-stage query-based framework for WikiData QA, proposing multi-stage approach that enhances performance on challenging multi-hop and temporal benchmarks. Through generalization and rejection studies, we evaluate robustness across multi-hop and temporal QA datasets. Additionally, we introduce a novel entity linking and predicate matching method using CoT reasoning. Our results demonstrate the potential of query-based multi-stage KGQA framework for improving multi-hop and temporal QA with small language models. Code and data: https://github.com/ar2max/NLDB-KGQA-System","short_abstract":"Large language models excel in question-answering (QA) yet still struggle with multi-hop reasoning and temporal questions. Query-based knowledge graph QA (KGQA) offers a modular alternative by generating executable queries instead of direct answers. We explore multi-stage query-based framework for WikiData QA, proposin...","url_abs":"https://arxiv.org/abs/2507.11954","url_pdf":"https://arxiv.org/pdf/2507.11954v1","authors":"[\"Artem Alekseev\",\"Mikhail Chaichuk\",\"Miron Butko\",\"Alexander Panchenko\",\"Elena Tutubalina\",\"Oleg Somov\"]","published":"2025-07-16T06:41:03Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.LG\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false,"code_links":[{"ID":612070,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2893804,"paper_url":"https://arxiv.org/abs/2507.11954","paper_title":"The benefits of query-based KGQA systems for complex and temporal questions in LLM era","repo_url":"https://github.com/ar2max/NLDB-KGQA-System","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}