danield21 / coco

Mi Zhang, Tieyun Qian, Ting Zhang, Xin Miao: Towards Model Robustness: Generating Contextual Counterfactuals for Entities in Relation Extraction. WWW 2023.

CoCo

This repository contains (PyTorch) code and datasets for CoCo, described by the paper: Mi Zhang, Tieyun Qian, Ting Zhang, Xin Miao, Towards Model Robustness: Generating Contextual Counterfactuals for Entities in Relation Extraction. The ACM Web Conference 2023.

Setup

Install dependencies

Please install all the dependency packages using the following command:

pip install -r requirements.txt

Download and preprocess the datasets

Our experiments are based on four datasets: SemEval, TACRED, PubMed, ACE2005. Please find the links and pre-processing below:

• SemEval: We provide the processed SemEval dataset in the "data" folder.
• TACRED: We can't provide the TACRED dataset directly because of copyright, but the dataset can be downloaded in https://catalog.ldc.upenn.edu/LDC2018T24.
• PubMeb: We can't provide the PubMeb dataset directly because of copyright, but you can get the PubMed dataset via FTP as described in https://pubmed.ncbi.nlm.nih.gov/download/.
• ACE05: We use the preprocessing code from DyGIE repo. Please follow the instructions to preprocess the ACE05 datasets.

Quick Start

The following commands can be used to genetate counterfactuals by SynCo and SemCo respectively.

# Run the SynCo moudle
python SynCo.py

# Run the SemCo moudle
python SemCo.py