Knowledge Base Question Answering

50 papers with code • 5 benchmarks • 10 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 )

Latest papers with no code

SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questions

no code yet • 16 Jul 2024

Much more complex than existing datasets, SPINACH calls for strong KBQA systems that do not rely on training data to learn the KB schema, but can dynamically explore large and often incomplete schemas and reason about them.

Robust Few-shot Transfer Learning for Knowledge Base Question Answering with Unanswerable Questions

no code yet • 20 Jun 2024

We present FUn-FuSIC that extends the state-of-the-art (SoTA) few-shot transfer model for answerable-only KBQA to handle unanswerability.

Temporal Knowledge Graph Question Answering: A Survey

no code yet • 20 Jun 2024

In response, this paper provides a thorough survey from two perspectives: the taxonomy of temporal questions and the methodological categorization for TKGQA.

A Learn-Then-Reason Model Towards Generalization in Knowledge Base Question Answering

no code yet • 20 Jun 2024

In order to improve the generalization capabilities of KBQA models, extensive research has embraced a retrieve-then-reason framework to retrieve relevant evidence for logical expression generation.

MASSIVE Multilingual Abstract Meaning Representation: A Dataset and Baselines for Hallucination Detection

no code yet • 29 May 2024

Abstract Meaning Representation (AMR) is a semantic formalism that captures the core meaning of an utterance.

Interactive-KBQA: Multi-Turn Interactions for Knowledge Base Question Answering with Large Language Models

no code yet • 23 Feb 2024

For each category of complex question, we devised exemplars to guide LLMs through the reasoning processes.

Triad: A Framework Leveraging a Multi-Role LLM-based Agent to Solve Knowledge Base Question Answering

no code yet • 22 Feb 2024

We 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. 8% and 20. 7%, respectively.

Clue-Guided Path Exploration: An Efficient Knowledge Base Question-Answering Framework with Low Computational Resource Consumption

no code yet • 24 Jan 2024

In this paper, we introduce a Clue-Guided Path Exploration framework (CGPE) that efficiently merges a knowledge base with an LLM, placing less stringent requirements on the model's capabilities.

How Proficient Are Large Language Models in Formal Languages? An In-Depth Insight for Knowledge Base Question Answering

no code yet • 11 Jan 2024

A typical approach to KBQA is semantic parsing, which translates a question into an executable logical form in a formal language.

In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models

no code yet • 6 Nov 2023

However, generating the most appropriate knowledge base query code based on Natural Language Questions (NLQ) poses a significant challenge in KBQA.