Learning to Identify Metaphors from a Corpus of Proverbs

نویسندگان

  • Gözde Özbal
  • Carlo Strapparava
  • Serra Sinem Tekiroglu
  • Daniele Pighin
چکیده

In this paper, we experiment with a resource consisting of metaphorically annotated proverbs on the task of word-level metaphor recognition. We observe that existing feature sets do not perform well on this data. We design a novel set of features to better capture the peculiar nature of proverbs and we demonstrate that these new features are significantly more effective on the metaphorically dense proverb data.

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تاریخ انتشار 2016