Metaphors are not only remarkably pervasive in both informal and formal text, but reflect fundamental properties of human cognition. This paper presents an algorithmic model that suggests metaphoric means of referring to concepts. For example, given a word such as "government", the method may propose expressions such as "father", "nanny", corresponding to common ways of thinking about the government. To achieve this, the model draws on MetaNet, a manually created repository of conceptual metaphor, in conjunction with lexical resources like FrameNet and WordNet and automated interlinking techniques. These resources are connected and their overall graph structure allows us to propose potential metaphoric means of referring to the given input words, possibly constrained with additional metaphoric seed words, which may be provided as supplementary inputs. The experiments show that this algorithm greatly expands the potential of the repository.
@InProceedings{DE MELO18.967, author = {Gerard De Melo}, title = "{Metaphor Suggestions based on a Semantic Metaphor Repository}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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