TeamZ: Measuring Semantic Textual Similarity for Spanish Using an Overlap-Based Approach

Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pages 633–635, Dublin, Ireland, August 23-24, 2014. TeamZ: Measuring Semantic Textual Similarity for Spanish Using an Overlap-Based Approach Anubhav Gupta UFR SLHS Universit´e de Franche-Comt´e anubhav.gupta@edu.univ-fcomte.fr Abstract This paper presents an overlap-based ap- proach using bag of words and the Spanish WordNet to solve the STS-Spanish sub- task (STS-Es) of SemEval-2014 Task 10. Since bag of words is the most commonly used method to ascertain similarity, the performance is modest. 1 Introduction The objective of STS-Es is to score a pair of sen- tences in Spanish on the scale of 0 (the two sen- tences are on different topics) to 4 (the two sen- tences are completely equivalent, as they mean the same thing) (Agirre et al., 2014). The textual sim- ilarity finds its utility in various NLP applications such as information retrieval, text categorisation, word sense disambiguation, text summarisation, topic detection, etc. (Besanc¸on et al., 1999; Mi- halcea et al., 2006; Islam and Inkpen, 2008). The method presented in this paper calculates the similarity based on the number of words that are common in two given sentences. This ap- proach, being simplistic, suffers from various drawbacks. Firstly, the semantically similar sen- tences need not have many words in common (Li et al., 2006). Secondly, even if the sentences have many words in common, the context in which they are used can be different (Sahami and Heilman, 2006). For example, based on the bag of words ap- proach, the sentences in Table 1 would be scored the same: However, only sentences [2] and [3] mean the same. Despite the flaws, this approach was used be- cause of the Basic Principle of Compositional- ity (Zimmermann, 2011), which states that the This work is licensed under a Creative Commons At- tribution 4.0 International Licence. Page numbers and pro- ceedings footer are added by the organisers. Licence details: http://creativecommons.org/licenses/by/4.0/ No. Spanish English 1 ´El es listo. He is clever. 2 ´El est´a listo. He is ready. 3 ´El est´a preparado. He is prepared. Table 1: Examples. meaning of a complex expression depends upon the meaning of its components and the man- ner in which they are composed. Furthermore, mainly nouns were considered in the bag of words because Spanish is an exocentric language, and nouns contain more specific, concrete semantic information than verbs (Michael Herslund, 2010; Michael Herslund, 2012). 2 Methodology The training dataset provided for the task con- sisted of 65 pairs of sentences along with their cor- responding similarity scores. There were two test sets: one consisted of 480 sentence pairs from a news corpus, and the other had 324 sentence pairs taken from Wikipedia. The approach consisted of learning the scoring with the help of linear regression. Two runs were submitted as solutions. The first run used three- feature vectors, whereas the second one used four- feature vectors. The features are the Jaccard in- dices for the lemmas, noun lemmas, synsets, and noun subjects in each sentence pair. For …

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