Humor processing is still a less studied issue, both in NLP and AI. In this paper we contribute to this field. In our previous research\r\nwe showed that adding a simple pun generator to a chatterbot can significantly improve its performance. The pun generator we\r\nused generated only puns based on words (not phrases). In this paper we introduce the next stage of the systemââ?¬â?¢s developmentââ?¬â?\r\nan algorithm allowing generation of phrasal pun candidates. We show that by using only the Internet (without any hand-made\r\nhumor-oriented lexicons), it is possible to generate puns based on complex phrases. As the output list is often excessively long,\r\nwe also propose a method for reducing the number of candidates by comparing two web-query-based rankings. The evaluation\r\nexperiment showed that the system achieved an accuracy of 72.5% for finding proper candidates in general, and the reduction\r\nmethod allowed us to significantly shorten the candidates list. The parameters of the reduction algorithm are variable, so that the\r\nbalance between the number of candidates and the quality of output can be manipulated according to needs.
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