Inferring the scope of negation in biomedical documents

Authors:
Miguel Ballesteros;Virginia Francisco;Alberto Díaz;Jesús Herrera;Pablo Gervás
Affiliations:
Departamento de Ingeniería del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain;Instituto de Tecnología del Conocimiento, Universidad Complutense de Madrid, Madrid, Spain;Departamento de Ingeniería del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain;Departamento de Ingeniería del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain;Instituto de Tecnología del Conocimiento, Universidad Complutense de Madrid, Madrid, Spain
Venue:
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Year:
2012

Citing 8
Cited 2

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ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
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IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics

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SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
A hybrid approach to finding negated and uncertain expressions in biomedical documents

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Abstract

In the last few years negation detection systems for biomedical texts have been developed successfully. In this paper we present a system that finds and annotates the scope of negation in English sentences. It infers which words are affected by negations by browsing dependency syntactic structures. Thus, firstly a greedy algorithm detects negation cues, like no or not. And secondly the scope of these negation cues is computed. We tested the system over the Bioscope corpus, annotated with negation, obtaining competitive results. The system presented in this paper can be accessed via web.