QUDeval: Evaluating Questions Under Discussion Discourse Parsing

Welcome to the official repository for the EMNLP 2023 paper, "QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing."

Authors: Yating Wu, Ritika Mangla, Greg Durrett, and Junyi Jessy Li

If you find our work useful or relevant to your research, please consider citing our paper.

@inproceedings{wu2023qudeval,
  title={QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing},
  author={Wu, Yating and Mangla, Ritika and Durrett, Greg and Li, Junyi Jessy},
  booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
  pages={5344--5363},
  year={2023}
}

Introduction 🌟

This work introduces the first framework for the automatic evaluation of QUD parsing, instantiating the theoretical constraints of QUD in a concrete protocol.

Table of Contents 📚

0. Code for Data Collection
1. Data Collection
2. Code for Evaluation

Code for Data Collection 📁

The code can be found under this repo

Data Collection 📥

The data is placed under the data folder.

Code for Evaluation 🖥️

The code can be found under code folder