Метафораны анықтау

In this paper, we propose a textual clue ap- proach to help metaphor detection, in order to improve the semantic processing of this figure. The previous works in the domain …...

AbstractMethods for automatic detection and interpretation of metaphors have focused on analysis and utilization of the ways in which metaphors violate selectional preferences (Martin, 2006). Detection and interpretation processes that …...

AbstractIn this work, we present the Language Computer Corporation (LCC) annotated metaphor datasets, which represent the largest and most comprehensive resource for metaphor research to date. These datasets were produced …...

Metaphor is a common linguistic tool in communication, making its detection in discourse a crucial task for natural lan- guage understanding. One popular ap- proach to this challenge is to …...

AbstractIn this paper we describe experiments with automated detection of metaphors in the Polish language. We focus our analysis on noun phrases composed of an adjective and a noun, and …...

AbstractMetaphor detection has been both challenging and rewarding in natural language processing applications. This study offers a new approach based on eventive information in detecting metaphors by leveraging the Chinese …...

AbstractNon-literal language phenomena such as idioms or metaphors are commonly studied in isolation from each other in NLP. However, often similar definitions and features are being used for different phenomena, …...

AbstractWe present new results on Metaphor Detection by using text from visual datasets. Using a straightforward technique for sampling text from Vision-Language datasets, we create a data structure we term …...

AbstractMetaphor as a cognitive mechanism in human’s conceptual system manifests itself an effective way for language communication. Although being intuitively sensible for human, metaphor detection is still a challenging task …...

Detecting metaphors is challenging due to the subtle ontological differences between metaphorical and non-metaphorical expres- sions. Neural networks have been widely adopted in metaphor detection and become the main stream …...

This paper focuses on utilizing metaphor inter- pretation to enhance metaphor detection. Con- sidering that existing approaches to metaphor interpretation are limited by ambiguous mean- ings of the metaphorical substitute …...

AbstractMetaphor detection plays an important role in tasks such as machine translation and human-machine dialogue. As more users express their opinions on products or other topics on socialmedia through metaphorical …...

AbstractCorrect natural language understanding requires computers to distinguish the literal and metaphorical senses of a word. Recent neu- ral models achieve progress on verb metaphor detection by viewing it as …...

AbstractIn this paper we present MisNet, a novel model for word level metaphor detection. MisNet converts two linguistic rules, i.e., Metaphor Identification Procedure (MIP) and Selectional Preference Violation (SPV) into …...

AbstractMetaphors use words from one domain of knowledge to describe another, which can make the meaning less clear and require human interpretation to understand. This makes it difficult for automated …...

AbstractNon-compositional expressions present a substantial challenge for natural language processing (NLP) systems, necessitating more intricate processing compared to general language tasks, even with large pre-trained language models. Their non-compositional nature …...

AbstractWe propose a novel RoBERTa-based model, RoPPT, which introduces a target-oriented parse tree structure in metaphor detection. Compared to existing models, RoPPT focuses on semantically relevant information and achieves the …...