Enhancing Temporal Knowledge Graph Forecasting with Large Language Models via Chain-of-History Reasoning

arXiv:2402.14382v1 Announce Type: new
Abstract: Temporal Knowledge Graph (TKG) forecasting aims to predict future facts based on given histories. Most recent graph-based models excel at capturing structural information within TKGs but lack semantic comprehension abilities. Nowadays, with the surge of LLMs, the LLM-based TKG prediction model has emerged. However, the existing LLM-based model exhibits three shortcomings: (1) It only focuses on the first-order history for prediction while ignoring high-order historical information, resulting in the provided information for LLMs being extremely …

abstract arxiv cs.cl excel facts forecasting future graph graph-based history information knowledge knowledge graph language language models large language large language models llm llms prediction reasoning semantic temporal type via