PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A metalearning approach to processing the scope of negation
Roser Morante and Walter Daelemans
In: CoNLL 2009, 4 June 2009, Boulder, Colorado, USA.

Abstract

Finding negation signals and their scope in text is an important subtask in information extraction. In this paper we present a machine learning system that finds the scope of negation in biomedical texts. The system combines several classifiers and works in two phases. To investigate the robustness of the approach, the system is tested on the three subcorpora of the BioScope corpus representing different text types. It achieves the best results to date for this task, with an error reduction of 32.07% compared to current state of the art results.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:5755
Deposited By:Roser Morante
Deposited On:08 March 2010