REA Prompt for Zero-Shot Relation Extraction

This repository contains the implementation and experimental framework for the paper “REA: Refine-Estimate-Answer Prompting for Zero-Shot Relation Extraction,” focusing on enhancing machine understanding of unstructured text without prior training data.

Quick Start 🚀

Prerequisites 📋

• Python 3.10 or higher
• CUDA-capable GPU for efficient model computation

Installation 🔧

1. Set up a Python virtual environment:

   conda create -n REA python=3.10
   conda activate REA
   

2. Install dependencies:

   pip install -r requirements.txt
   

Running the Experiments 🧪

Local Execution

Execute the experiments locally using:

python main.py --model_id your_model_id --top_p your_top_p --temperature your_temperature --task your_task --setting your_setting --access_token your_access_token --rel_size your_rel_size

📦 Cluster Execution with SLURM

For cluster environments using SLURM:

1. Prepare the Apptainer container (SIF_FILE.sif) in your directory.
2. Build the Apptainer container using the provided my_apptainer.def file:

   # Build the Apptainer container
   apptainer build SIF_FILE.sif my_apptainer.def

3. Run the REA experiments within the Apptainer container by submitting the SLURM chain_job:

   sbatch chain_job.sh

This script leverages a single GPU and runs experiments for up to 48 hours.

Data 📊

Utilize these datasets:

• TACRED
• FewRel
• Wiki-ZSL

Place your dataset files in designated directories as outlined in main.py.

Contributing 🤝

Contributions are welcome! Please submit pull requests or open issues for improvements or bug fixes.

Paper 📄

You can access the full paper at the following link: Original Paper.

BibTeX Citation

@inproceedings{layegh2024rea,
  title={REA: Refine-Estimate-Answer Prompting for Zero-Shot Relation Extraction},
  author={Layegh, Amirhossein and Payberah, Amir H and Matskin, Mihhail},
  booktitle={International Conference on Applications of Natural Language to Information Systems},
  pages={301--316},
  year={2024},
  organization={Springer}
}