Paper: BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment

ACL ID S14-2021
Title BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

The results obtained by the BUAP team at Task 1 of SemEval 2014 are presented in this paper. The run submitted is a supervised ver- sion based on two classification models: 1) We used logistic regression for determining the semantic relatedness between a pair of sentences, and 2) We employed support vec- tor machines for identifying textual entailment degree between the two sentences. The be- haviour for the second subtask (textual entail- ment) obtained much better performance than the one evaluated at the first subtask (related- ness), ranking our approach in the 7th position of 18 teams that participated at the competi- tion.