CACN-EMNLP-2023

This repository contains the code and resources related to the paper "From Chaos to Clarity: Claim Normalization to Empower Fact-Checking". If you find our work helpful, please consider citing our paper:

 @article{sundriyal2023chaos,
    title={From Chaos to Clarity: Claim Normalization to Empower Fact-Checking},
    author={Sundriyal, Megha and Chakraborty, Tanmoy and Nakov, Preslav},
    journal={arXiv preprint arXiv:2310.14338},
    year={2023}
    }

Getting Started

Dataset

A sample of the dataset is provided in the CLAN-samples.csv file. Please note that this is just a small subset for demonstration purposes. If you need the complete dataset, please contact the authors.

How to Run

| Step 1: Clone the Repository

git clone https://github.com/LCS2-IIITD/CACN-EMNLP-2023.git

| Step 2: Navigate to the Project Directory

cd CACN-EMNLP-2023

| Step 3: Install the Required Packages

. openai == 0.28.0
. pandas == 1.5.3
. csv == 1.0
. re == 2.2.1
. nltk == 3.8.1

| Step 4: Set Up Configuration Add your OpenAI API key at the designated place, i.e. <add-your-key-here>.

| Step 5: Run the Main Script

python cacn.py