TalkDown: A Corpus for Condescension Detection in Context

Introduction

This is the code release for the paper TalkDown: A Corpus for Condescension Detection in Context by Zijian Wang and Christopher Potts in proceedings of EMNLP-IJCNLP 2019.

Dependencies

Python dependencies

Run pip install -r requirements.txt. This codebase requires Python version >= 3.6.

Data

Run bash download_data.bash to download and uncompress the TalkDown dataset. Or you could use this link.

Pretrained model (optional)

Run bash download_model.bash to download our best pretrained model to reproduce the result. It is not required if you want to train your model from scratch.

Sample commands for training and evaluation

Train

You could train a BERT model using the following command.

python -m src.bert --do_train --use_quoted --use_context --output_dir test

Evaluate

You could evaluate your model using the following command. This command also reproduces our best result in the paper (make sure you have downloaded the pretrained model).

python -m src.bert --do_eval --use_quoted --use_context --eval_on_test --output_dir pretrained_full

which should return Model's F1 is 0.6835111677776263

Citation

@inproceedings{wang2019talkdown,
  author = {Wang, Zijian  and  Potts, Christopher}
  title = {{TalkDown}: A Corpus for Condescension Detection in Context},
  booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing},
  url = {https://www.aclweb.org/anthology/D19-1385},
  year = {2019}
}

Contact

You may reach out us at zijwang@stanford.edu and cgpotts@stanford.edu.