Goal-Oriented Script Construction

Qing Lyu, Li Zhang, Chris Callison-Burch


Abstract
The knowledge of scripts, common chains of events in stereotypical scenarios, is a valuable asset for task-oriented natural language understanding systems. We propose the Goal-Oriented Script Construction task, where a model produces a sequence of steps to accomplish a given goal. We pilot our task on the first multilingual script learning dataset supporting 18 languages collected from wikiHow, a website containing half a million how-to articles. For baselines, we consider both a generation-based approach using a language model and a retrieval-based approach by first retrieving the relevant steps from a large candidate pool and then ordering them. We show that our task is practical, feasible but challenging for state-of-the-art Transformer models, and that our methods can be readily deployed for various other datasets and domains with decent zero-shot performance.
Anthology ID:
2021.inlg-1.19
Original:
2021.inlg-1.19v1
Version 2:
2021.inlg-1.19v2
Volume:
Proceedings of the 14th International Conference on Natural Language Generation
Month:
August
Year:
2021
Address:
Aberdeen, Scotland, UK
Editors:
Anya Belz, Angela Fan, Ehud Reiter, Yaji Sripada
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
184–200
Language:
URL:
https://aclanthology.org/2021.inlg-1.19
DOI:
10.18653/v1/2021.inlg-1.19
Bibkey:
Cite (ACL):
Qing Lyu, Li Zhang, and Chris Callison-Burch. 2021. Goal-Oriented Script Construction. In Proceedings of the 14th International Conference on Natural Language Generation, pages 184–200, Aberdeen, Scotland, UK. Association for Computational Linguistics.
Cite (Informal):
Goal-Oriented Script Construction (Lyu et al., INLG 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/add_acl24_videos/2021.inlg-1.19.pdf
Supplementary attachment:
 2021.inlg-1.19.Supplementary_Attachment.zip
Code
 veronica320/wikihow-gosc
Data
WikiHow