@inproceedings{3985caa0f55b458cb98b23dd8c29bb6b,
title = "UNAL-NLP: Combining Soft Cardinality Features for Semantic Textual Similarity, Relatedness and Entailment",
abstract = "This paper describes our participation in the SemEval-2014 tasks 1, 3 and 10. We used an uniform approach for addressing all the tasks using the soft cardinality for extracting features from text pairs, and machine learning for predicting the gold standards. Our submitted systems ranked among the top systems in all the task and sub-tasks in which we participated. These results confirm the results obtained in previous SemEval campaigns suggesting that the soft cardinality is a simple and useful tool for addressing a wide range of natural language processing problems.",
author = "Sergio Jimenez and George Due{\~n}as and Julia Baquero and Alexander Gelbukh",
note = "Publisher Copyright: {\textcopyright} 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings. All rights reserved.; 8th International Workshop on Semantic Evaluation, SemEval 2014 ; Conference date: 23-08-2014 Through 24-08-2014",
year = "2014",
language = "Ingl{\'e}s",
series = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "732--742",
editor = "Preslav Nakov and Torsten Zesch",
booktitle = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
}