Abstract
In this paper we introduce computational model for recognizing figurative expressions in Japanese language. As a part of the training data we use the set of almost 26,000 Japanese sentences comprising both similes and metaphors. These were collected manually from literary texts and hence constitute trustworthy and probably the largest existing resource of its kind. We use the data for classification task to evaluate its usability for figurativeness recognition. Precision score achieved by one of the classifiers utilized during the test shows that our model outperforms state-of-the-art methods in this aspect.
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Babieno, M., Rzepka, R., Araki, K. (2020). Evaluating Classification Algorithms for Recognizing Figurative Expressions in Japanese Literary Texts. In: Nguyen, LM., Phan, XH., Hasida, K., Tojo, S. (eds) Computational Linguistics. PACLING 2019. Communications in Computer and Information Science, vol 1215. Springer, Singapore. https://doi.org/10.1007/978-981-15-6168-9_16
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DOI: https://doi.org/10.1007/978-981-15-6168-9_16
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