TnT-LLM: Text Mining at Scale with Large Language Models

arXiv:2403.12173v1 Announce Type: new
Abstract: Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and application. However, most existing methods for producing label taxonomies and building text-based label classifiers still rely heavily on domain expertise and manual curation, making the process expensive and time-consuming. This is particularly challenging when the label space is under-specified and large-scale data annotations are unavailable. In this paper, we address these …

abstract analysis application arxiv building classifiers cs.ai cs.cl cs.ir domain expertise forms however labels language language models large language large language models llm mining scale taxonomies text type unstructured