The Lesk model had an accuracy of 56%, which is lower than that of a naïve polysemy model which simply selects the punchline with the highest mean polysemy (66%) and even of a random-choice baseline (62%).
it should be stressed here that the Lesk model did not directly account for the possibility that any given word might be ambiguous.