@inproceedings{choubey-etal-2020-discourse,
title = "Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event",
author = "Choubey, Prafulla Kumar and
Lee, Aaron and
Huang, Ruihong and
Wang, Lu",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.478",
doi = "10.18653/v1/2020.acl-main.478",
pages = "5374--5386",
abstract = "Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional discourse structure for news articles that revolves around the main event and create a human-annotated corpus of 802 documents spanning over four domains and three media sources. Next, we propose several document-level neural-network models to automatically construct news content structures. Finally, we demonstrate that incorporating system predicted news structures yields new state-of-the-art performance for event coreference resolution. The news documents we annotated are openly available and the annotations are publicly released for future research.",
}
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<abstract>Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional discourse structure for news articles that revolves around the main event and create a human-annotated corpus of 802 documents spanning over four domains and three media sources. Next, we propose several document-level neural-network models to automatically construct news content structures. Finally, we demonstrate that incorporating system predicted news structures yields new state-of-the-art performance for event coreference resolution. The news documents we annotated are openly available and the annotations are publicly released for future research.</abstract>
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%0 Conference Proceedings
%T Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event
%A Choubey, Prafulla Kumar
%A Lee, Aaron
%A Huang, Ruihong
%A Wang, Lu
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F choubey-etal-2020-discourse
%X Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional discourse structure for news articles that revolves around the main event and create a human-annotated corpus of 802 documents spanning over four domains and three media sources. Next, we propose several document-level neural-network models to automatically construct news content structures. Finally, we demonstrate that incorporating system predicted news structures yields new state-of-the-art performance for event coreference resolution. The news documents we annotated are openly available and the annotations are publicly released for future research.
%R 10.18653/v1/2020.acl-main.478
%U https://aclanthology.org/2020.acl-main.478
%U https://doi.org/10.18653/v1/2020.acl-main.478
%P 5374-5386
Markdown (Informal)
[Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event](https://aclanthology.org/2020.acl-main.478) (Choubey et al., ACL 2020)
ACL