Creating a Fine Grained Entity Type Taxonomy Using LLMs

arXiv:2402.12557v1 Announce Type: new
Abstract: In this study, we investigate the potential of GPT-4 and its advanced iteration, GPT-4 Turbo, in autonomously developing a detailed entity type taxonomy. Our objective is to construct a comprehensive taxonomy, starting from a broad classification of entity types - including objects, time, locations, organizations, events, actions, and subjects - similar to existing manually curated taxonomies. This classification is then progressively refined through iterative prompting techniques, leveraging GPT-4's internal knowledge base. The result is an …

abstract advanced arxiv classification construct cs.cl events gpt gpt-4 iteration llms locations objects organizations study taxonomy turbo type types