Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching

• [2024-12-01] 🎉 Our paper has been accepted at COLING 2025.

Entity matching (EM) is a critical step in entity resolution (ER). Recently, entity matching based on large language models (LLMs) has shown great promise. However, current LLM-based entity matching approaches typically follow a binary matching paradigm that ignores the global consistency between record relationships. In this paper, we investigate various methodologies for LLM-based entity matching that incorporate record interactions from different perspectives. Specifically, we comprehensively compare three representative strategies: matching, comparing, and selecting, and analyze their respective advantages and challenges in diverse scenarios. Based on our findings, we further design a compound entity matching framework (ComEM) that leverages the composition of multiple strategies and LLMs. ComEM benefits from the advantages of different sides and achieves improvements in both effectiveness and efficiency. Experimental results on 8 ER datasets and 9 LLMs verify the superiority of incorporating record interactions through the selecting strategy, as well as the further cost-effectiveness brought by ComEM.

First, install dependencies and prepare the data

# clone project git clone https://github.com/tshu-w/ComEM.git cd ComEM # [SUGGESTED] use conda environment conda env create -f environment.yaml conda activate llm4em # [ALTERNATIVE] install requirements directly pip install -r requirements.txt # prepare the data git clone https://github.com/AI-team-UoA/pyJedAI data/pyJedAI python src/blocking.py

Next, to obtain the main results of the paper:

python src/{strategy}.py

@inproceedings{wang-etal-2025-match, title = "Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching", author = "Wang, Tianshu and Chen, Xiaoyang and Lin, Hongyu and Chen, Xuanang and Han, Xianpei and Sun, Le and Wang, Hao and Zeng, Zhenyu", editor = "Rambow, Owen and Wanner, Leo and Apidianaki, Marianna and Al-Khalifa, Hend and Eugenio, Barbara Di and Schockaert, Steven", booktitle = "Proceedings of the 31st International Conference on Computational Linguistics", month = jan, year = "2025", address = "Abu Dhabi, UAE", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2025.coling-main.8/", pages = "96--109", }