Paper: ECNUCS: Recognizing Cross-lingual Textual Entailment Using Multiple Text Similarity and Text Difference Measures

ACL ID S13-2021
Title ECNUCS: Recognizing Cross-lingual Textual Entailment Using Multiple Text Similarity and Text Difference Measures
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper presents our approach used for cross-lingual textual entailment task (task 8) organized within SemEval 2013. Cross- lingual textual entailment (CLTE) tries to de- tect the entailment relationship between two text fragments in different languages. We solved this problem in three steps. Firstly, we use a off-the-shelf machine translation (MT) tool to convert the two input texts into the same language. Then after performing a text preprocessing, we extract multiple feature types with respect to surface text and gram- mar. We also propose novel feature types regarding to sentence difference and seman- tic similarity based on our observations in the preliminary experiments. Finally, we adopt a multiclass SVM algorithm for classification. The results on the cross-lingual data collec- ...