PunFields at SemEval-2017 Task 7: Employing Roget's Thesaurus in Automatic Pun Recognition and Interpretation

TL;DR

This paper presents PunFields, a model for automatic pun recognition and interpretation using Roget's Thesaurus, which identifies semantic fields in puns and employs machine learning for classification, showing promising results with room for improvement.

Contribution

The paper introduces PunFields, a novel approach combining semantic field detection and machine learning for pun recognition and interpretation.

Findings

Good performance in pun classification

Effective semantic field detection

Needs improvement in target word search

Abstract

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.