Knowledge Base Question Answering
46 papers with code • 5 benchmarks • 9 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Knowledge Base Question Answering
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Datasets
WebQuestionsSP
ComplexWebQuestions
FrenchMedMCQA
VANiLLa
Latest papers
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family
tan92hl/complex-question-answering-evaluation-of-chatgpt
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ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge.
Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question Alignment
tttttttty/alcqa
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Complex knowledge base question answering can be achieved by converting questions into sequences of predefined actions.
Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments
dki-lab/pangu
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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.
A Sequential Flow Control Framework for Multi-hop Knowledge Base Question Answering
xie-minghui/gfc
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Conference 2022
One of the key challenges of knowledge base question answering (KBQA) is the multi-hop reasoning.
ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering
dki-lab/arcaneqa
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COLING 2022
Question answering on knowledge bases (KBQA) poses a unique challenge for semantic parsing research due to two intertwined challenges: large search space and ambiguities in schema linking.
Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering
ruckbreasoning/subgraphretrievalkbqa
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ACL 2022
Recent works on knowledge base question answering (KBQA) retrieve subgraphs for easier reasoning.
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs
Question answering (QA) over knowledge bases (KBs) is challenging because of the diverse, essentially unbounded, types of reasoning patterns needed.
Injecting Numerical Reasoning Skills into Knowledge Base Question Answering Models
Embedding-based methods are popular for Knowledge Base Question Answering (KBQA), but few current models have numerical reasoning skills and thus struggle to answer ordinal constrained questions.
Improving Embedded Knowledge Graph Multi-hop Question Answering by introducing Relational Chain Reasoning
Knowledge Graph Question Answering (KGQA) aims to answer user-questions from a knowledge graph (KG) by identifying the reasoning relations between topic entity and answer.
RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering
salesforce/rng-kbqa
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ACL 2022
We present RnG-KBQA, a Rank-and-Generate approach for KBQA, which remedies the coverage issue with a generation model while preserving a strong generalization capability.
