# Using Language Models For Knowledge Acquisition in Natural Language Reasoning Problems

**Authors:** Fangzhen Lin, Ziyi Shou, Chengcai Chen  
**arXiv:** [2304.01771](https://arxiv.org/abs/2304.01771)  
**Date:** 2023-04-04  
**Summary page:** https://www.summarizepaper.com/fr/paper/2304.01771v1/

## Abstract

For a natural language problem that requires some non-trivial reasoning to solve, there are at least two ways to do it using a large language model (LLM). One is to ask it to solve it directly. The other is to use it to extract the facts from the problem text and then use a theorem prover to solve it. In this note, we compare the two methods using ChatGPT and GPT4 on a series of logic word puzzles, and conclude that the latter is the right approach.