Opposite Information Annotation on ‘Word List by Semantic Principles’

Abstract

This paper presents research on opposite information annotation on the thesaurus ‘Word List by Semantic Principles (WLSP)’. The categorised words with the same label include antonym word pairs. We extract the opposite word pairs from the categorised group and classified the opposite word pairs. Firstly, the annotators manually extracted opposite word pair candidates. Secondly, we utilised Yahoo! crowdsourcing to evaluate how many people recognise the opposite word pair as the opposites. We defined ‘opposites’ as the words judged by greater than or equal to 50% people. Thirdly, we annotated the opposites types by Muraki for the word pairs. We analysed the opposite word lists by their asymmetry, the label of WLSP, the opposite types, their frequencies and word embeddings. In the linguistic point of view, the closed opposite word pairs tend to be regarded as ‘opposites’. In the natural language processing point of view, the distances between two words in the opposite pairs correlates their replaceability of the human judge.