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

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.
Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP 2016)
USA
Association for Computational Linguistics
978-1-945626-25-8
Ozbal, Gozde; Strapparava, Carlo; Tekiroglu, Serra; Pighin, Daniele
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.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/343192
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? ND
social impact