Abstract
We propose a system that has been initially used for Recognising Textual Entailment (RTE). Due to the fact that these two tasks (AVE and RTE) rely on the same main idea, our system was considered appropriate to be applied to AVE. Our system represents texts by means of logic forms and computes the semantic similarity between them. We have also designed a voting strategy between our system and the MLEnt system also developed at the University of Alicante. Although the results have not been very high, we consider them quite promising. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Ferrández, Ó., Terol, R. M., Muñoz, R., Martínez-Barco, P., & Palomar, M. (2007). A knowledge-based textual entailment approach applied to the AVE task. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4730 LNCS, pp. 490–493). Springer Verlag. https://doi.org/10.1007/978-3-540-74999-8_58
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
