Models of Metaphor in NLP
نویسنده
چکیده
Automatic processing of metaphor can be clearly divided into two subtasks: metaphor recognition (distinguishing between literal and metaphorical language in a text) and metaphor interpretation (identifying the intended literal meaning of a metaphorical expression). Both of them have been repeatedly addressed in NLP. This paper is the first comprehensive and systematic review of the existing computational models of metaphor, the issues of metaphor annotation in corpora and the available resources.
منابع مشابه
Detecting Metaphor by Contextual Analogy
As one of the most challenging issues in NLP, metaphor identification and its interpretation have seen many models and methods proposed. This paper presents a study on metaphor identification based on the semantic similarity between literal and non literal meanings of words that can appear at the same context.
متن کاملBlack Holes and White Rabbits: Metaphor Identification with Visual Features
Metaphor is pervasive in our communication, which makes it an important problem for natural language processing (NLP). Numerous approaches to metaphor processing have thus been proposed, all of which relied on linguistic features and textual data to construct their models. Human metaphor comprehension is, however, known to rely on both our linguistic and perceptual experience, and vision can pl...
متن کاملTextual Entailment as an Evaluation Framework for Metaphor Resolution: A Proposal
We aim to address two complementary deficiencies in Natural Language Processing (NLP) research: (i) Despite the importance and prevalence of metaphor across many discourse genres, and metaphor’s many functions, applied NLP has mostly not addressed metaphor understanding. But, conversely, (ii) difficult issues in metaphor understanding have hindered large-scale application, extensive empirical e...
متن کاملStatistical Metaphor Processing
Metaphor is highly frequent in language, which makes its computational processing indispensable for real-world NLP applications addressing semantic tasks. Previous approaches to metaphor modelling rely on task-specific hand-coded knowledge and operate on a limited domain or a subset of phenomena. We present the first integrated open-domain statistical model of metaphor processing in unrestricte...
متن کاملMetaphor Identification as Interpretation
Automatic metaphor identification and interpretation in text have been traditionally considered as two separate tasks in natural language processing (NLP) and addressed individually within computational frameworks. However, cognitive evidence suggests that humans are likely to perform these two tasks simultaneously, as part of a holistic metaphor comprehension process. We present a novel method...
متن کامل