Code and Dataset for our ACL 2023 Paper "Knowing-how & Knowing-that: A New Task for Machine Reading Comprehension of User Manuals".
We propose the Knowing-how & Knowing-that task that requires the model to answer various questions about a user manual. We resolve it by representing the steps and facts of a user manual in a unified graph named TARA. To benchmark it, we design an efficient method and annotate a testing set derived from real-world customer service scenarios.
Code and dataset are provided by Ant Group. The dataset has been reviewed and filtered by the company and does not contain any personal privacy information of the user.
If you find TARA useful for your research and applications, please kindly cite using this BibTeX:
@inproceedings{liang2023knowing,
title={Knowing-how \& Knowing-that: A New Task for Machine Comprehension of User Manuals},
author={Liang, Hongru and Liu, Jia and Du, Weihong and Jin, Dingnan and Lei, Wenqiang and Wen, Zujie and Lv, Jiancheng},
booktitle={Findings of the Association for Computational Linguistics: ACL 2023},
pages={10550--10564},
year={2023}
}