Deep learning approach for negation trigger and scope recognition

Hermenegildo Fabregat, Lourdes Araujo, Juan Martínez-Romo


The automatic detection of negation elements is an active area of study due to its high impact on several natural language processing tasks. This article presents a system based on deep learning and a non-language dependent architecture for the automatic detection of both, triggers and scopes of negation for English and Spanish. The presented system obtains for English comparable results with those obtained in recent works by more complex systems. For Spanish, the results obtained in the detection of negation triggers are remarkable. The results for the scope recognition are similar to those obtained for English.

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