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We present two novel datasets for the low-resource language Vietnamese toassess models of semantic similarity: ViCon comprises pairs of synonyms andantonyms across word classes, thus offering data to distinguish betweensimilarity and dissimilarity. ViSim-400 provides degrees of similarity acrossfive semantic relations, as rated by human judges. The two datasets areverified through standard co-occurrence and neural network models, showingresults comparable to the respective English datasets.

Introducing two Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and Relatedness