Our first data set, containing English homographic puns, is the one described by Miller & Turković (2016) and Miller (2016). It contains punning and non-punning jokes, aphorisms, and other short texts sourced from professional humorists and online collections, and is licensed under the Creative Commons Attribution-Noncommercial (CC BY-NC) licence. The second data set of heterographic puns is currently under construction. Both data sets will be provided in an XML format similar to that used in previous Senseval/SemEval WSD tasks.
For Subtask 3, participants must apply senses from version 3.1 of WordNet, an electronic semantic network. However, they are not limited to the use of WordNet for this subtask, nor for any other subtasks. For all subtasks involving the second data set, participants may wish to make additional use of lexical-semantic resources that include pronunciation information, such as Wiktionary or the CMU Pronouncing Dictionary. This is because heterographic puns present an additional challenge to the interpretation process; in these puns the target (second meaning) has a different spelling and, usually, a different yet similar-sounding pronunciation.
Computational recovery of the target lexeme must be achieved not only via computational lexical semantics but through the application of some computational model of sound similarity. Implementations of general-purpose sound similarity models such as Soundex (Knuth, 1973:391–392) and Metaphone (Philips, 1990) are already widely available. Participants may alternatively wish to avail themselves of more sophisticated models developed for use with computational detection of cognates, surveys of which can be found in Kondrak (2002) and Kondrak & Sherif (2006), or with puns (Hempelmann, 2003). Machine-readable data for implementing Hempelmann's pun-based model of sound similarity will be made freely available to participants.