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

arXiv:2402.15131v1 Announce Type: new
Abstract: This study explores the realm of knowledge-base question answering (KBQA). KBQA is considered a challenging task, particularly in parsing intricate questions into executable logical forms. Traditional semantic parsing (SP)-based methods require extensive data annotations, which result in significant costs. Recently, the advent of few-shot in-context learning, powered by large language models (LLMs), has showcased promising capabilities. Yet, fully leveraging LLMs to parse questions into logical forms in low-resource scenarios poses a substantial challenge. To tackle …

abstract annotations arxiv costs cs.ai cs.cl data forms interactions interactive knowledge knowledge base language language models large language large language models parsing question question answering questions semantic study type