Semantic lexical similarity and relatedness are important issues in natural language processing (NLP). Similarity and relatedness are not the same, while they are very closely related. To date, in many works these two issues are mixed up which harm system’s effectiveness. A popular approach to measure semantic similarity and relatedness is utilizing WordNet, a lexical database. This paper shows that Wordnet’s gloss is a potential source for measuring semantic relatedness. Experiment result using WordSim353 relatedness database confirms the effectiveness of the approach.