SemEval-2017 Task 7: Detection and Interpretation of English Puns

Abstract

A pun is a form of wordplay in which a word suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another word, for an intended humorous or rhetorical effect. Though a recurrent and expected feature in many discourse types, puns stymie traditional approaches to computational lexical semantics because they violate their one-sense-percontext assumption. This paper describes the first competitive evaluation for the automatic detection, location, and interpretation of puns. We describe the motivation for these tasks, the evaluation methods, and the manually annotated data set. Finally, we present an overview and discussion of the participating systems' methodologies, resources, and results.

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

“…The size of the context window is (0; +3) for verbs, (0;+2) for adjectives; (-2;+2) for nouns, adverbs, and other parts of speech within the sentence where a word is used. Table 6 illustrates SemEval results (Miller et al, 2017) of our system PunFields 8 (Ho. -homographic, He.…”

JU CSE NLP $@$ SemEval 2017 Task 7: Employing Rules to Detect and Interpret English Puns

“…In the present shared task (Miller et al, 2017), participants are provided with a trial dataset and a test dataset. No training data was supplied due to the large cardinality of such words or contexts in general.…”

BuzzSaw at SemEval-2017 Task 7: Global vs. Local Context for Interpreting and Locating Homographic English Puns with Sense Embeddings

“…A recently proposed set of artificial intelligence tasks (Miller et al, 2017) challenges computers to try their hand at it: pun detection (tell whether or not a text contains a pun), pun location (given a text with a pun, tell which word is the pun) and pun interpretation (given a pun in context, tell which senses it evokes).…”