TnT-LLM: Automating Text Taxonomy Generation and Classification With Large Language Models

We begin with a high-level overview of TnT-LLM, our proposed two-phase framework for 1) LLM-powered taxonomy generation and 2) LLM-augmented text classification.

Table of Links

Abstract and 1 Introduction

2 Related Work

3 Method and 3.1 Phase 1: Taxonomy Generation

3.2 Phase 2: LLM-Augmented Text Classification

4 Evaluation Suite and 4.1 Phase 1 Evaluation Strategies

4.2 Phase 2 Evaluation Strategies

5 Experiments and 5.1 Data

5.2 Taxonomy Generation

5.3 LLM-Augmented Text Classification

5.4 Summary of Findings and Suggestions

6 Discussion and Future Work, and References

A. Taxonomies

B. Additional Results

C. Implementation Details

D. Prompt Templates

3 METHOD

We begin with a high-level overview of TnT-LLM, our proposed two-phase framework for 1) LLM-powered taxonomy generation and 2) LLM-augmented text classification. In the first phase, we sample a small-scale representative subset of a corpus ...