Due to the development of smart devices, the ability of computers to understand human language has become a key issue in technology. By learning and analyzing machine-readable, annotated linguistic data, computers are able to comprehend human language (corpus). Corpora plays a crucial role in helping computers comprehend human language. Metaphor is one of the most complicated linguistic data that computers cannot comprehend. Despite the prevalence of metaphor in everyday language use and the importance of identifying it, no corpus has been published for Persian yet. Compiling a corpus of Persian metaphors is the initial step in learning metaphors for computers. To compile a corpus of Persian metaphors, it is necessary to meet two main criteria. Deciding the best definition is the first prerequisite. The best definition is both comprehensive and applicable; comprehensive in the sense that it covers a significant proportion of metaphorical instances, and applicable in the sense that it could be used to build a corpus. The second requirement is the construction of a method for metaphor identification. Without a straightforward data annotation method, it is impossible to identify metaphors.
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Miri, M. S. (2023). Metaphor Annotation Criteria: A Step towards Building a Metaphor Corpus. ZABANPAZHUHI (Journal of Language Research), 15(47), 263-293. doi: 10.22051/jlr.2022.40681.2192
MLA
Mohammad Saeid Miri. "Metaphor Annotation Criteria: A Step towards Building a Metaphor Corpus", ZABANPAZHUHI (Journal of Language Research), 15, 47, 2023, 263-293. doi: 10.22051/jlr.2022.40681.2192
HARVARD
Miri, M. S. (2023). 'Metaphor Annotation Criteria: A Step towards Building a Metaphor Corpus', ZABANPAZHUHI (Journal of Language Research), 15(47), pp. 263-293. doi: 10.22051/jlr.2022.40681.2192
VANCOUVER
Miri, M. S. Metaphor Annotation Criteria: A Step towards Building a Metaphor Corpus. ZABANPAZHUHI (Journal of Language Research), 2023; 15(47): 263-293. doi: 10.22051/jlr.2022.40681.2192