The paper describes our search for a universal algorithm of detecting intentional lexical ambiguity in different forms of creative language. At SemEval-2018 Task 3, we used PunFields, the system of automatic analysis of English puns that we introduced at SemEval-2017, to detect irony in tweets. Preliminary tests showed that it can reach the score of F1=0.596. However, at the competition, its result was F1=0.549.

The article describes a model of automatic interpretation of English puns, based on Roget’s Thesaurus, and its implementation, PunFields. In a pun, the algorithm discovers two groups of words that belong to two main semantic fields. The fields become a semantic vector based on which an SVM classifier learns to recognize puns. A rule-based model is then applied for recognition of intentionally ambiguous (target) words and their definitions. In SemEval Task 7 PunFields shows a considerably good result in pun classification, but requires improvement in searching for the target word and its definition.