@inproceedings{mikhalkova-karyakin-2017-punfields,
    title = "{P}un{F}ields at {S}em{E}val-2017 Task 7: Employing {R}oget`s Thesaurus in Automatic Pun Recognition and Interpretation",
    author = "Mikhalkova, Elena  and
      Karyakin, Yuri",
    editor = "Bethard, Steven  and
      Carpuat, Marine  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/S17-2072/",
    doi = "10.18653/v1/S17-2072",
    pages = "426--431",
    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."
}