Multi-hop Question Answering over Knowledge Graphs using Large Language Models

arXiv:2404.19234v1 Announce Type: cross
Abstract: Knowledge graphs (KGs) are large datasets with specific structures representing large knowledge bases (KB) where each node represents a key entity and relations amongst them are typed edges. Natural language queries formed to extract information from a KB entail starting from specific nodes and reasoning over multiple edges of the corresponding KG to arrive at the correct set of answer nodes. Traditional approaches of question answering on KG are based on (a) semantic parsing (SP), …

abstract arxiv cs.ai cs.cl cs.db datasets extract graphs information key knowledge knowledge graphs language language models large datasets large language large language models natural natural language natural language queries node nodes queries question question answering reasoning relations them type