Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today’s massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a ‘story’. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.
- Edited by Tommaso Caselli, University of Groningen, Eduard Hovy, Carnegie Mellon University, Pennsylvania, Martha Palmer, University of Colorado Boulder, Piek Vossen, Vrije Universiteit, Amsterdam
- Publisher: Cambridge University Press
- Online publication date: November 2021
- Print publication year: 2021
- Online ISBN: 9781108854221
- DOI: https://doi.org/10.1017/9781108854221