Browse State-of-the-Art › Knowledge Base Question Answering
Knowledge Base Question Answering
67 papers with code · 10 benchmarks · 15 datasets archive 2025-07-28
Knowledge Base Q&A is the task of answering questions from a knowledge base.
( Image credit: Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering )
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
15 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 67 papers with code (136 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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16 Jul 2024 2 repositories listedSPINACH achieves a new state of the art on the QALD-7, QALD-9 Plus and QALD-10 datasets by 31.
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14 Mar 2023 2 repositories listedChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge.
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19 Dec 2022 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)Most existing work for grounded language understanding uses LMs to directly generate plans that can be executed in the environment to achieve the desired effects.
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1 Nov 2021 2 repositories listedThe high-level decoding generates an AQG as a constraint to prune the search space and reduce the locally ambiguous query graph.
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4 Sep 2019 2 repositories listed Syntology ran 1 of 12 samples · 11 unverifiedCommonsense reasoning aims to empower machines with the human ability to make presumptions about ordinary situations in our daily life.
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6 Mar 2019 2 repositories listed Syntology ran 0 of 11 samples · 11 unverifiedWhen answering natural language questions over knowledge bases (KBs), different question components and KB aspects play different roles.
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6 Dec 2018 2 repositories listedSecond, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.
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18 Feb 2025 1 repository listedKnowledge base question answering (KBQA) aims to answer user questions in natural language using rich human knowledge stored in large KBs.
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31 Jan 2025 1 repository listed Syntology ran 2 of 8 samples · 6 unverifiedMoreover, it employs MCTS, a heuristic search method driven by policy and reward models, to balance agentic exploration's performance and search space.
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24 Dec 2024 1 repository listedRetrieval from graph data is crucial for augmenting large language models (LLM) with both open-domain knowledge and private enterprise data, and it is also a key component in the recent GraphRAG system (edge et al.,…
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18 Oct 2024 1 repository listed Syntology ran 1 of 12 samples · 11 unverifiedIn order to improve the efficiency, PoG prunes irrelevant information from the graph exploration first and introduces efficient three-step pruning techniques that incorporate graph structures, LLM prompting, and a…
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1 Oct 2024 1 repository listedWe apply the grammar to knowledge base question answering, where the constraints by candidate expressions assist a semantic parser to generate valid KB elements.
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5 Aug 2024 1 repository listedAdvancements in AI and natural language processing have revolutionized machine-human language interactions, with question answering (QA) systems playing a pivotal role.
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29 Jun 2024 1 repository listedExisting KBQA methods have traditionally relied on multi-stage methodologies, involving tasks such as entity linking, subgraph retrieval and query structure generation.
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26 Jun 2024 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)Based on preference data, DPA-RAG accomplishes both external and internal preference alignment: 1) It jointly integrate pair-wise, point-wise, and contrastive preference alignment abilities into the reranker, achieving…
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16 Mar 2024 1 repository listedAn essential requirement for a real-world Knowledge Base Question Answering (KBQA) system is the ability to detect the answerability of questions when generating logical forms.
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23 Feb 2024 1 repository listed Syntology ran 7 of 10 samples · 3 unverified · 10 pointer-only (licence)To tackle these hurdles, we introduce Interactive-KBQA, a framework designed to generate logical forms through direct interaction with knowledge bases (KBs).
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22 Feb 2024 1 repository listed Syntology ran 5 of 5 samples · 0 unverifiedWe evaluated the performance of our framework using three benchmark datasets, and the results show that our framework outperforms state-of-the-art systems on the LC-QuAD and YAGO-QA benchmarks, yielding F1 scores of 11.
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24 Jan 2024 1 repository listedMost existing methods use a paradigm that treats the question as the objective, with relevant knowledge being incrementally retrieved from the knowledge graph.
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19 Dec 2023 1 repository listedTo address this issue, we construct a \textbf{dual relation graph} where each node denotes a relation in the original KG (\textbf{primal entity graph}) and edges are constructed between relations sharing same head or…
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15 Nov 2023 1 repository listedAdditional experiments show that FuSIC-KBQA also outperforms SoTA KBQA models in the in-domain setting when training data is limited.
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6 Nov 2023 1 repository listedWe present the dataset GeoQuestions1089 for benchmarking geospatial question answering engines.
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13 Oct 2023 1 repository listed Syntology ran 8 of 16 samples · 8 unverifiedKnowledge Base Question Answering (KBQA) aims to answer natural language questions over large-scale knowledge bases (KBs), which can be summarized into two crucial steps: knowledge retrieval and semantic parsing.
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15 Sep 2023 1 repository listedLanguage models (LMs) have already demonstrated remarkable abilities in understanding and generating both natural and formal language.
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28 Aug 2023 1 repository listed Syntology ran 10 of 10 samples · 0 unverified · 10 pointer-only (licence)Knowledge Base Question Answering (KBQA) aims to answer natural language questions with factual information such as entities and relations in KBs.
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23 Aug 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverifiedKnowledge base question answering (KBQA) is a critical yet challenging task due to the vast number of entities within knowledge bases and the diversity of natural language questions posed by users.
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15 Aug 2023 1 repository listedThis paper explores GPT-3 for answering natural language questions over Linked Data.
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13 Jun 2023 1 repository listedTo verify that QDT can enhance KBQA task, we design a decomposition-based KBQA system called QDTQA.
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31 May 2023 1 repository listedIn this work we present a system, developed for the European Space Agency (ESA), that can answer complex natural language queries, to support engineers in accessing the information contained in a KB that models the…
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23 May 2023 1 repository listedBy pairing our semantic parser with GPT-3, we combine verifiable results with qualified GPT-3 guesses to provide useful answers to 96% of the questions in dev.
Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections