Martin Atkinson


2018

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On Training Classifiers for Linking Event Templates
Jakub Piskorski | Fredi Šarić | Vanni Zavarella | Martin Atkinson
Proceedings of the Workshop Events and Stories in the News 2018

The paper reports on exploring various machine learning techniques and a range of textual and meta-data features to train classifiers for linking related event templates automatically extracted from online news. With the best model using textual features only we achieved 94.7% (92.9%) F1 score on GOLD (SILVER) dataset. These figures were further improved to 98.6% (GOLD) and 97% (SILVER) F1 score by adding meta-data features, mainly thanks to the strong discriminatory power of automatically extracted geographical information related to events.

2017

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On the Creation of a Security-Related Event Corpus
Martin Atkinson | Jakub Piskorski | Hristo Tanev | Vanni Zavarella
Proceedings of the Events and Stories in the News Workshop

This paper reports on an effort of creating a corpus of structured information on security-related events automatically extracted from on-line news, part of which has been manually curated. The main motivation behind this effort is to provide material to the NLP community working on event extraction that could be used both for training and evaluation purposes.

2012

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ONTS: “Optima” News Translation System
Marco Turchi | Martin Atkinson | Alastair Wilcox | Brett Crawley | Stefano Bucci | Ralf Steinberger | Erik Van der Goot
Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics

2011

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Exploring the Usefulness of Cross-lingual Information Fusion for Refining Real-time News Event Extraction: A Preliminary Study
Jakub Piskorski | Jenya Belayeva | Martin Atkinson
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

2008

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Online-Monitoring of Security-Related Events
Martin Atkinson | Jakub Piskorski | Bruno Pouliquen | Ralf Steinberger | Hristo Tanev | Vanni Zavarella
Coling 2008: Companion volume: Demonstrations