Modality and Negation in Event Extraction
Abstract
Language provides speakers with a rich system of modality for expressing thoughts about events, without being committed to their actual occurrence. Modality is commonly used in the political news domain, where both actual and possible courses of events are discussed. NLP systems struggle with these semantic phenomena, often incorrectly extracting events which did not happen, which can lead to issues in downstream applications. We present an open-domain, lexicon-based event extraction system that captures various types of modality. This information is valuable for Question Answering, Knowledge Graph construction and Fact-checking tasks, and our evaluation shows that the system is sufficiently strong to be used in downstream applications.
Cite
@article{arxiv.2109.09393,
title = {Modality and Negation in Event Extraction},
author = {Sander Bijl de Vroe and Liane Guillou and Miloš Stanojević and Nick McKenna and Mark Steedman},
journal= {arXiv preprint arXiv:2109.09393},
year = {2021}
}
Comments
S. Bijl de Vroe, L. Guillou, M. Stanojevi\'c, N. McKenna, and M. Steedman. 2021. Modality and Negation in Event Extraction. In Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021), pages 31-42, online. Association for Computational Linguistics