  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.
