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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
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 documentlevel neural-network models to automatically construct news contentdoi:10.18653/v1/2020.acl-main.478 fatcat:ceon52mc5fh2vhnqku45guh73a