Prompting Large Language Models with Knowledge Graphs for Question Answering Involving Long-tail Facts

arXiv:2405.06524v1 Announce Type: new
Abstract: Although Large Language Models (LLMs) are effective in performing various NLP tasks, they still struggle to handle tasks that require extensive, real-world knowledge, especially when dealing with long-tail facts (facts related to long-tail entities). This limitation highlights the need to supplement LLMs with non-parametric knowledge. To address this issue, we analysed the effects of different types of non-parametric knowledge, including textual passage and knowledge graphs (KGs). Since LLMs have probably seen the majority of factual …

abstract arxiv cs.cl facts graphs highlights knowledge knowledge graphs language language models large language large language models llms nlp prompting question question answering struggle tasks type world