@inproceedings{song-etal-2017-discourse,
title = "Discourse Mode Identification in Essays",
author = "Song, Wei and
Wang, Dong and
Fu, Ruiji and
Liu, Lizhen and
Liu, Ting and
Hu, Guoping",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-1011",
doi = "10.18653/v1/P17-1011",
pages = "112--122",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Discourse Mode Identification in Essays
%A Song, Wei
%A Wang, Dong
%A Fu, Ruiji
%A Liu, Lizhen
%A Liu, Ting
%A Hu, Guoping
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F song-etal-2017-discourse
%X 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.
%R 10.18653/v1/P17-1011
%U https://aclanthology.org/P17-1011
%U https://doi.org/10.18653/v1/P17-1011
%P 112-122
Markdown (Informal)
[Discourse Mode Identification in Essays](https://aclanthology.org/P17-1011) (Song et al., ACL 2017)
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.