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.
Learning to Identify Metaphors from a Corpus of Proverbs / Ozbal, Gozde; Strapparava, Carlo; Tekiroglu, Serra; Pighin, Daniele. - (2016), pp. 2060-2065. (Intervento presentato al convegno Conference on Empirical Methods in Natural Language Processing (EMNLP 2016) tenutosi a Austin, Texas, USA nel November 1–5, 2016).
Learning to Identify Metaphors from a Corpus of Proverbs
Ozbal Gozde;Strapparava Carlo;Tekiroglu Serra;Pighin Daniele
2016-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
