Temporal Processing of News

The ability to capture the temporal dimension of a natural language text is essential to many Natural Language Processing applications, such as Question Answering, Automatic Summarisation, and Information Retrieval. Temporal Processing is a field of Computational Linguistics which aims to access this dimension and derive a precise temporal representation of a natural language text by extracting time expressions, events and temporal relations, and then representing them according to a chosen knowledge framework. This book focuses on the investigation and understanding of the different ways time is expressed in natural language, on the implementation of a temporal processing system in accordance with the results of this investigation, on the evaluation of the system, and on the extensive analysis of the errors and challenges that appear during system development. The ultimate goal of this research is to develop the ability to automatically annotate temporal expressions, verbal events and temporal relations in a natural language text.

Autorentext

Dr. Georgiana Marsic holds a PhD in Computational Linguistics from University of Wolverhampton, UK, an MSc in Computational Linguistics and a BSc in Computer Science from Al. I. Cuzä University, Romania. Georgiana is currently working as a Research Fellow for the University of Wolverhampton and for the National Board of Medical Examiners, USA.