Discourse Mode Identification in Essays

Wei Song, Dong Wang, Ruiji Fu, Lizhen Liu, Ting Liu, Guoping Hu


Abstract
Discourse modes play an important role in writing composition and evaluation. This paper presents a study on the manual and automatic identification of narration,exposition, description, argument and emotion expressing sentences in narrative essays. We annotate a corpus to study the characteristics of discourse modes and describe a neural sequence labeling model for identification. Evaluation results show that discourse modes can be identified automatically with an average F1-score of 0.7. We further demonstrate that discourse modes can be used as features that improve automatic essay scoring (AES). The impacts of discourse modes for AES are also discussed.
Anthology ID:
P17-1011
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
112–122
Language:
URL:
https://aclanthology.org/P17-1011
DOI:
10.18653/v1/P17-1011
Bibkey:
Cite (ACL):
Wei Song, Dong Wang, Ruiji Fu, Lizhen Liu, Ting Liu, and Guoping Hu. 2017. Discourse Mode Identification in Essays. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 112–122, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Discourse Mode Identification in Essays (Song et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-1011.pdf
Video:
 https://aclanthology.org/P17-1011.mp4