We investigate the effectiveness of semantic generalizations/classifications for capturing the regularities of the behavior of verbs in terms of their metaphoricity. Starting from orthographic word unigrams, we experiment with various ways of defining semantic classes for verbs (grammatical, resource-based, distributional) and measure the effectiveness of these classes for classifying all verbs in a running text as metaphor or non metaphor.
REF uses binary classification of the verbs into metaphorical or literal using semantic classes of the verbs such as grammatical, resource-based, or distributional.
Semantic classifications for detection of verb metaphors
ACL
Computer Science