A Proposal for Linguistic Similarity Datasets Based on Commonality Lists

Understand

Similarity is a core notion that is used in psychology and two branches of linguistics: theoretical and computational.

• The similarity datasets that come from the two fields differ in design: psychological datasets are focused around a certain topic such as fruit names, while linguistic datasets contain words from various categories.
• The later makes humans assign low similarity scores to the words that have nothing in common and to the words that have contrast in meaning, making similarity scores ambiguous.
• In this work we discuss the similarity collection procedure for a multi-category dataset that avoids score ambiguity and suggest changes to the evaluation procedure to reflect the insights of psychological literature for word, phrase and sentence similarity.