In the last decade, the problem of computational metaphor processing has garnered
immense attention from the domains of computational linguistics and cognition. A wide …

We present and compare two alternative deep neural architectures to perform word-level
metaphor detection on text: a bi-LSTM model and a new structure based on recursive feed …

Metaphor identification helps improve the performance of various natural language
understanding tasks such as word sense disambiguation and sentiment analysis. Though …

Automatic processing of figurative languages is gaining popularity in NLP community for
their ubiquitous nature and increasing volume. In this era of web 2.0, automatic analysis of …

We present a corpus of 240 argumentative essays written by non-native speakers of English
annotated for metaphor. The corpus is made publicly available. We provide benchmark …

This paper reports a linguistically-enriched method of detecting token-level metaphors for
the second shared task on Metaphor Detection. We participate in all four phases of …

Metaphors are a common linguistic phenomenon, and metaphor identification plays an
essential role in metaphor processing. Most existing metaphor computing techniques use …

Metaphors convey unspoken emotions and perceptions by creatively applying an evocative
concept from the source domain to illustrate some latent idea in the target domain. Prior …

“Metaphor is booming business”(Steen, Dorst et al. 2010b 1: 1). is statement is as true today
as it was years ago when it rst appeared in the groundbreaking volume, A method for …

Identification of metaphoric language in text is critical for generating effective semantic
representations for natural language understanding. Computational approaches to …